Topic 7: Neural Networks and Deep Learning 2592


Title (link) Author Date Votes Error Reviews
A Character-Level Decoder without Explicit Segmentation for Neural Machine Translation Junyoung Chung, Kyunghyun Cho, Yoshua Bengio 2016
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Convolutional Sequence to Sequence Learning Jonas Gehring, Michael Auli, David Grangier, Denis Yarats, Yann N. Dauphin 2017
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Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks Jun-Yan Zhu, Taesung Park, Phillip Isola, Alexei A. Efros 2017
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TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems Martin Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, et al. 2016
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Incorporating Structural Alignment Biases into an Attentional Neural Translation Model Trevor Cohn, Cong Duy Vu Hoang, Ekaterina Vymolova, Kaisheng Yao, Chris Dyer, Gholamreza Haffari 2016
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Leveraging Word Embeddings for Spoken Document Summarization Kuan-Yu Chen, Shih-Hung Liu, Hsin-Min Wang, Berlin Chen, Hsin-Hsi Chen 2015
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Better Summarization Evaluation with Word Embeddings for ROUGE Jun-Ping Ng, Viktoria Abrecht 2015
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Abstractive Sentence Summarization with Attentive Recurrent Neural Networks Sumit Chopra, Michael Auli, Alexander M. Rush 2016
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AttSum: Joint Learning of Focusing and Summarization with Neural Attention Ziqiang Cao, Wenjie Li, Sujian Li, Furu Wei 2016
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Generating News Headlines with Recurrent Neural Networks Konstantin Lopyrev 2015
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Modelling, visualising and summarising documents with a single convolutional neural network Misha Denil, Alban Demiraj, Nal Kalchbrenner, Phil Blunsom, Nando de Freitas 2014
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A Convolutional Attention Network for Extreme Summarization of Source Code Miltiadis Allamanis, Hao Peng, Charles Sutton 2016
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Distraction-Based Neural Networks for Document Summarization Qian Chen, Xiaodan Zhu, Zhenhua Ling, Si Wei, Hui Jiang 2016
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SummaRuNNer: A Recurrent Neural Network based Sequence Model for Extractive Summarization of Documents Ramesh Nallapati, Feifei Zhai, Bowen Zhou 2016
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Neural Network-Based Abstract Generation for Opinions and Arguments Lu Wang, Wang Ling 2016
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Neural sentence ordering Xinchi Chen, Xipeng Qiu, Xuanjing Huang 2016
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Tensorflow: Large-scale machine learning on heterogeneous distributed systems Mart?n Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, others 2016
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Recurrent Neural Networks Stephen Grossberg 2013
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Temporal Difference Learning Andrew Barto 2007
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Title (link) Author Date Votes Error Reviews
Deep Learning for NLP Richard Socher, Yoshua Bengio and Chris Manning 2012
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Deep Learning Geoff Hinton, Yoshua Bengio & Yann LeCun 2015
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Anyone Can Learn To Code an LSTM-RNN in Python (Part 1:RNN) Andrew Trask 2015
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Understanding LSTM Networks Christopher Olah 2015
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Long short-term memory Wikipedia 2017
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Visual Analysis for State Changes in RNNs Sebastian Gerhrmann, Hendrik Strobelt, Bernd Huber, Hanspeter Pfister, Alexander M. Rush 2016
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LSTM Netowrks for Sentiment Analysis Pierre Luc Carrier, Kyunghyun Cho 2015
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LSTM implementation explained Adam Paszke 2015
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Building Autoencoders in Keras Francois Chollet 2016
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Concrete Author Unknown 2017
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Embedding Methods for NLP Part 1: Unsupervised and Supervised Embeddings Jason Weston, Antoine Bordes 2014
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Deep Learning for Natural Language Processing Ronan Collobert, Jason Weston 2009
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Deep Learning & Neural Networks Lecture 1 Kevin Duh 2014
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Deep Learning & Neural Networks Lecture 2 Kevin Duh 2014
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Deep Learning & Neural Networks Lecture 3 Kevin Duh 2014
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Deep Learning & Neural Networks Lecture 4 Kevin Duh 2014
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Deep Learning Tutorial Kevin Duh 2015
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Deep Learning for Natural Language Processing: Theory and Practice Xiaodong He, Jianfeng Gao, Li Deng 2014
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A Course in Machine Learning Hal Daume III 2015
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Using Neural Networks for Modelling and Representing Natural Languages Tomas Mikolov 2014
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Dublin School DL4MT: Deep Learning for Machine Translation Hermann Ney, Tamer Alkhouli, Kazuki Irie, Jan-Thorsten Peter 2015
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Deep Learning for Natural Language Processing and Related Applications Xiaodong He, Jianfeng Gao, and Li Deng 2014
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Deep Learning Tutorial Yann LeCun, MarcAurelio Ranzato 2013
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Neural Machine Translation Thang Luong, Kyunghyun Cho, Christopher Manning 2016
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Grokking Deep Learning Andrew W. Trask 2016
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Sentences as Matrices and Translating with Attention Chris Dyer 2016
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Continuous Vector Spaces for Cross-Language NLP Applications Rafael E. Banchs 2016
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Practical Neural Networks for NLP Part 1 Chris Dyer, Yoav Goldberg, Graham Neubig 2016
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Practical Neural Networks for NLP Part 2 Chris Dyer, Yoav Goldberg, Graham Neubig 2016
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Implementing a Neural Network from Scratch in Python - An Introduction Denny Britz 2015
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A Neural Network in 11 lines of Python (Part 1). A bare bones neural network implementation to describe the inner workings of backpropagation. Andrew Trask 2015
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A Neural Network in 13 lines of Python (Part 2 - Gradient Descent). Improving our neural network by optimizing Gradient Descent. Andrew Trask 2015
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A Complete Guide on Getting Started with Deep Learning in Python Faizan Shaikh 2016
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UFLDL Tutorial Andrew Ng, Jiquan Ngiam, Chuan Yu Foo, Yifan Mai, Caroline Suen 2013
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Evaluating Goal-oriented End-to-End Dialog Systems Antoine Bordes, Jason Weston, Y-Lan Boureau, Jesse Dodge, Andre Gane, Xiang Zhang, Alex Miller, Arthur Szlam, Sumit Chopra 2016
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Scaling Machine Learning with TensorFlow Jeff Dean 2015
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Theano Tutorial Colin Raffel 2017
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Deep Learning Tutorials LISA lab 2017
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Derivatives in Theano LISA lab 2017
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Theano - Tutorial LISA lab 2017
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Practical Guide to implementing Neural Networks in Python (using Theano) Aarshay Jain 2016
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Beginner Tutorial: Neural Nets in Theano Brandon B 2015
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Theano Tutorial Marek Rei 2016
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Natural Language Understanding Kyunghyun Cho 2016
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Neural Networks Rob Fergus 2015
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Natural Language Understanding: Foundations and State-of-the-Art Percy Liang 2015
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Deep Learning I: Supervised Learning Russ Salakhutdinov 2017
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Deep Learning II: Unsupervised Learning Russ Salakhutdinov 2017
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Deep Learning III: Unsupervised Learning Russ Salakhutdinov 2017
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Deep Learning IV: Model Evaluations and Open Questions Russ Salakhutdinov 2017
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Word Embedding Explained and Visualized Xin Rong 2015
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From Sequence Modeling to Translation Kyunghyun Cho 2015
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Compositional Distributional Models of Meaning Dimitri Kartsaklis and Mehrnoosh Sadrzadeh 2016
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Neural networks for natural language understanding Sam Bowman, Chris Potts, and Chris Manning 2015
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Neural language models and word embeddings Piotr Mirowski 2014
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Recurrent Neural Networks Tutorial, Part 1 - Introduction to RNNs Denny Britz 2015
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Recurrent Neural Networks Tutorial, Part 2 - Implementing a RNN with Python, Numpy, and Theano Denny Britz 2015
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Recurrent Neural Networks Tutorial, Part 3- Backpropagation Through Time and Vanishing Gradients Denny Britz 2015
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Deep Learning Transcends the Bag of Words Zachary Lipton 2015
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Excellent Tutorial on Sequence Learning using Recurrent Neural Networks Gregory Piatetsky 2015
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Recurrent Neural Networks Tutorial, Introduction Denny Britz 2015
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Introduction to Recurrent Networks in TensorFlow Danijar Hafner 2016
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Practical Examples for RNNs in Tensorflow Denny Britz 2016
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RNNetwork Tutorial: Part 2 - Implementing a RNN in Python and Theano Denny Britz 2016
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Parsey Universal Slav Petrov 2016
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Deep Learning with Spark and TensorFlow Tim Hunter 2016
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TensorFlow Playground Daniel Smilkov, Shan Carter 2017
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Image Recognition TensorFlow, 2016
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An Introduction to Generative Adversarial Networks (with code in TensorFlow) John Glover 2016
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An Introduction to Implementing Neural Networks using TensorFlow Faizan Shaikh 2016
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The Gentlest Introduction to Tensorflow - Part 1 Soon Hin Khor 2016
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The Gentlest Introduction to Tensorflow - Part 2 Soon Hin Khor 2016
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The Gentlest Introduction to Tensorflow - Part 3 Soon Hin Khor 2016
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Sequence-to-Sequence Models Ilya Sutskever 2014
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Recursive (not Recurrent!) Neural Networks in TensorFlow Alireza Nejati 2016
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Recursive (not recurrent!) Neural Nets in TensorFlow Alireza Nejati 2016
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Recurrent neural network handwriting generation demo Alex Graves 2014
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A Beginner's guide to Recurrent Networks and LSTMs Skymind 2015
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Recurrent Neural Network Tutorial, Part 4 – Implementing a GRU/LSTM RNN with Python and Theano Denny Britz 2015
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Dissecting Google's Billion Word Language Model Part 1: Character Embeddings Colin Morris 2016
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Google's trained Word2Vec model in Python Chris McCormick 2016
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ConvNetJS Denoising Autoencoder demo Andrej Karpathy 2014
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Autoencoders Andrew Maas 2013
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Theano, Autoencoders and MNIST The Triangle Inequality 2014
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ATTENTION AND MEMORY IN DEEP LEARNING AND NLP Denny Britz 2016
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Text summarization with TensorFlow Peter Liu, Xin Pan 2016
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Text Summarization in Python: Extractive vs. Abstractive techniques revisited Pranay Mathur, Aman Gill, Aayush Yadav 2017
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Multiprocessing with GPU in keras Krishna Kalyan 2017
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Tutorial: Optimizing Neural Networks using Keras (with Image recognition case study) Faizan Shaikh 2016
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How convolutional neural networks see the world Francois Chollet 2016
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Keras Cheat Sheet: Neural Networks in Python Karlijn Willems 2016
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FastText and Genism word embeddings Jayant Jain 2016
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Introduction to Word2Vec Skymind 2015
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Tips on Building Neural Machine Translation Systems Graham Neubig 2016
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Introduction to Neural Machine Translation with GPUs (part 2) Kyunghyun Cho 2016
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Introduction to Neural Machine Translation with GPUs (part 3) Kyunghyun Cho 2016
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Neural Machine Translation -ACL Thang Luong, Kyunghyun Cho, Christopher Manning 2016
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Deep Learning for Visual Question Answering Avi Singh 2015
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Understanding Convolutional Neural Networks for NLP Denny Britz 2015
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What is the difference between convolutional neural networks, restricted Boltzmann machines, and auto-encoders? ffriend 2015
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Understanding Convolutional Neural Networks for NLP Denny Britz 2015
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Understanding Convolutions Christopher Olah 2014
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Conv Nets: A Modular Perspective Christopher Olah 2014
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Peeking Inside Convolutional Neural Networks Audun M. Øygard 2016
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Inside Deep Learning Computer Vision Convolutional Neural Networks Nikhil Buduma 2015
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How do Convolutional Neural Networks work? Brandon Rohrer 2016
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Deep Learning for Computer Vision - Introduction to Convolution Neural Networks Aarshay Jain 2016
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An Intuitive Explanation of Convolutional Neural Networks Ujjwal Karn 2016
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Implementing a CNN for Text Classification in TensorFlow Denny Britz 2015
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An Intuitive Explanation of Convolutional Neural Networks Ujjwal Karn 2016
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A Beginner's Guide To Understanding Convolutional Neural Networks Adit Deshpande 2016
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A Beginner's Guide To Understanding Convolutional Neural Networks Part 2 Adit Deshpande 2016
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Deep Learning for Natural Language Processing Phil Blunsom 2017
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Deep Neural Networks Are Our Friends Phil Blunsom 2017
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Deep Learning for NLP: Word Vecotrs and Lexical Semantics Phil Blunsom 2017
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Deep Learning for Natural Language Processing Practicals Overview Chris Dyer 2017
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Recurrent Neural Networks and Language Modelling: Part 1 Phil Blunsom 2017
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Recurrent Neural Networks and Language Modelling: Part 2 Phil Blunsom 2017
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Deep Learning for Natural Language Processing Text Classification Karl Moritz Hermann 2017
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Hardware and Software for NLP Jeremy Appleyard 2017
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Conditional Language Modeling Chris Dyer 2017
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Conditional Language Modeling with Attention Chris Dyer 2017
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Question Answering Karl Moritz Hermann 2017
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Deep Learning for NLP: Memory Phil Blunsom 2017
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Deep Learning Tutorial Andrew Ng, Jiquan Ngiam, Chuan Yu Foo, Yifan Mai, Caroline Suen, Adam Coates, Andrew Maas, Awni Hannun, Brody Huval, Tao Wang, and Sameep Tandon 2013
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A noob’s guide to implementing RNN-LSTM using Tensorflow Monik Pamecha 2016
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A Neural Network in 11 lines of Python Andrew Trask 2015
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Evaluation of Deep Learning Toolkits Kenneth Tran 2015
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A Review of Popular Deep Learning Models Jason Toy 2016
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Implementing Neural Networks in Javascript Tine Wiederer 2016
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Deep Learning in Neural Networks: An Overview Adrian Colyer 2016
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Holding Your Hand Like a Small Child Through a Neural Network Part 1 Paul Singman 2016
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Holding Your Hand Like a Small Child Through a Neural Network Part 2 Paul Singman 2016
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Deep Learning from 30,000 feet Gregory Piatetsky 2016
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Must Know Tips for Deep Learning Neural Networks, Part 1 Xiu-Shen Wei 2016
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Must Know Tips for Deep Learning Neural Networks, Part 2 Xiu-Shen Wei 2016
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Learning to Code Neural Networks Per Harald Borgen 2016
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7 Steps to Understanding Deep Learning Matthew Mayo 2016
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Top 10 Deep Learning Tips & Tricks Anmol Rajpurohit 2015
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How do Neural Networks Learn? Michael Skirpan 2015
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A Statistical View of Deep Learning Shakir Mohamed 2015
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Unveiling the Hidden Layers of Deep Learning Amanda Montanez 2016
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Google DeepMind's AlphaGo: How it works Christopher Burger 2016
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Why Does Deep Learning Work? Charles H Martin 2015
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Deep Learning, The Curse of Dimensionality, and Autoencoders Nikhil Buduma 2015
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RE.WORK Deep Learning Summit, San Francisco, January – videos, presentations Gregory Piatetsky 2015
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Deep Learning in a Nutshell – what it is, how it works, why care? Nikhil Buduma 2015
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Multilayer Perceptron deeplearning.net 2017
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Neural Networks Part 1: Feedingforward and Backpropagation triangleinequality 2014
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Neural Networks Part 2: Python Implementation triangleinequality 2014
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Deep Learning Reading List Caglar Gulcehre 2016
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Public Webpage of LISA Frederic Bastien 2012
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Introducing Knet8: beginning deep learning with 100 lines of Julia Deniz Yuret 2016
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Julia, neural nets, parallelism, and parsing Deniz Yuret 2015
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How to learn about deep learning Deniz Yuret 2015
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Modern ML for NLP: Large Scale Techniques for Shallow and Deep Learning Part II: Deep Learning Techniques Dan Pressel 2016
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Image Completion with Deep Learning in TensorFlow Brandon Amos 2016
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Facebook’s Artificial Intelligence Research lab releases open source fastText on GitHub John Mannes 2016
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Memory Networks for Language Understanding Jason Weston 2016
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Neural Networks, Manifolds, and Topology Christopher Olah 2014
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Neural Networks, Types, and Functional Programming Christopher Olah 2015
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Visualizing Representations: Deep Learning and Human Beings Christopher Olah 2015
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Inceptionism: Going Deeper into Neural Networks Christopher Olah, Alexander Mordvintsev, Mike Tyka 2015
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Groups & Group Convolutions Christopher Olah 2014
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Visual Information Theory Christopher Olah 2015
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Interactive Tutorials Niraj Kumar 2016
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Decoding (neural?) representations Hal Daume 2016
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Unsupervised Deep Learning and Representation Learning Tutorial Denny Britz 2016
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Deep Natural Language Understanding Kyunghyun Cho 2016
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Deep Learning for NLP - Tutorial Nils Reimers 2016
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The Evolution and Core Concepts of Deep Learning & Neural Networks Guest Blog 2016
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Fundamentals of Deep Learning – Starting with Artificial Neural Network Aarshay Jain 2016
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Guest Post (Part I): Demystifying Deep Reinforcement Learning Tambet Matiisen 2015
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Deep Learning of Representations Yoshua Bengio 2013
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Recurrent Neural Networks with Word Embeddings Grégoire Mesnil 2013
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Deep Learning in a Nutshell: Core Concepts Tim Dettmers 2015
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Perceptron 5: XOR (how & why neurons work together) Author Unknown 2012
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ResNets, HighwayNets, and DenseNets, Oh My! Arthur Juliani 2016
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Tutorial on Deep Learning Ruslan Salakhutdinov 2017
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Deep Learning Research Review Week 2: Reinforcement Learning Adit Deshpande 2016
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The 9 Deep Learning Papers You Need To Know About (Understanding CNNs Part 3) Adit Deshpande 2016
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Contextual RNN-GANs for Abstract Reasoning Diagram Generation Arnab Ghosh, Viveka Kulharia, Amitabha Mukerjee, Vinay Namboodiri, Mohit Bansal 2016
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Generative Adversarial Networks (GANs) in 50 lines of code (PyTorch) Dev Nag 2017
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Polyglot: Distributed word representations for multilingual NLP Rami Al-Rfou, Bryan Perozzi, Steven Skiena 2013
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A Beginner’s Guide to Neural Networks with R! Jose Portilla 2016
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A Beginner’s Guide to Neural Networks with Python and SciKit Learn 0.18! Jose Portilla 2016
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Parallelism in Machine Learning: GPUs, CUDA, and Practical Applications Matthew Mayo 2016
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Tutorial - What is a variational autoencoder? Jaan Altosaar 2016
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The Neural Network Zoo Fjodor Van Veen 2014
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Artificial Neural Networks Introduction (PART II) Annalyn Ng 2016
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Build your own Deep Learning Box Annalyn Ng 2016
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Artificial Neural Networks (ANN) Introduction: Training a Computer to Recognize Your Handwriting Annalyn Ng 2016
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New neural network building block allows faster and more accurate text understanding James Bradbury, Stephen Merity, Caiming Xiong, and Richard Socher. 2016
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Introduction to seq2seq Anna Goldie, Denny Britz 2017
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Learning when to skim and when to read Alexander Rosenberg Johansen, Bryan McCann, James Bradbury, Richard Socher 2017
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How to Make a Text Summarizer - Intro to Deep Learning #10 Siraj Raval 2017
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Recurrent Neural Networks Google Brain 2017
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CS231n: Neural Networks Case Study Andrej Karpathy 2017
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A Quick Introduction to Neural Networks Ujjwal Karn 2016
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Deep Generative Models Ishaan Gulrajani 2017
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Deep Learning for Computer Vision Lex Fridman 2017
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Intro to Deep Learning Nick Locascio 2017
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Neural Machine Translation: Multilingual, Character-Level Machine Translation Kyunghyun Cho 2017
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Sequence Modeling with Neural Networks Harini Suresh 2017
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Representation Learning for Reading Comprehension Russ Salakhutdinov 2016
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Neural Text Embeddings for IR Bhaskar Mitra, Nick Craswell 2017
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Distributed Representations of Sentences and Documents Author Unknown 2014
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Pointer Networks in TensorFlow (with sample code) Dev Nag 2016
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The Extraordinary Link Between Deep Neural Networks and the Nature of the Universe Emerging Technology from the arXiv 2016
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TF-Slim: A high level library to define complex models in TensorFlow Nathan Silberman, Sergio Guadarrama 2016
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Train your own image classifier with Inception in TensorFlow Jon Shlens 2016
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Some notes on samping from character-level RBMs Colin Morris 2016
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Simple Genetic Algorithm In 15 Lines Of Python Brandon 2015
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Simple Genetic Algorithm in Python --Addendum Brandon 2015
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Implementing the DistBelief Deep Neural Network Training Framework with Akka Alex Minnaar 2015
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Introduction to Deep Learning Raghotham S, Bargava Subramanian 2013
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Multi-Layer Neural Network Andrew Ng, Jiquan Ngiam, Chuan Yu Foo, Yifan Mai, Caroline Suen, Adam Coates, Andrew Maas, Awni Hannun, Brody Huval, Tao Wang, Sameep Tandon 2013
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Multilayer Perceptron LISA Lab 2008
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A Beginner’s Tutorial for Restricted Boltzmann Machines Skymind 2017
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Deep Autoencoders Skymind 2017
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Denoising Autoencoders (dA) LISA Lab 2008
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Deep Learning Research Review: Reinforcement Learning Adit Deshpane 2016
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Deep Learning Research Review: Generative Adversarial Nets Adit Deshpane 2016
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Machine Learning Recipes with Josh Gordon Josh Gordon 2016
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Recurrent Neural Network models Adrian Coyler 2017
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Deep Learning for Stock Price Prediction Explained joe Ellsworth 2017
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The Mathematics of Machine Learning Wale Akinfaderin 2017
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Programming a Perceptron in Python Danilo Bargen 2013
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An Overview of Python Deep Learning Frameworks Madison May 2017
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How to Use Tensorflow for Seq2seq Models Siraj Raval 2017
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Deep learning with word2vec and gensim Radim Rehurek 2013
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Word2vec in Python, Part Two: Optimizing Radim Rehurek 2013
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Word2vec Tutorial Radim Rehurek 2014
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Making sense of word2vec Radim Rehurek 2014
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Doc2vec tutorial Radim Rehurek 2014
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WordRank embedding: "crowned" is most similar to "king", not word2vec’s "Canute" Parul Sethi 2017
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RRP #1: Tomas Mikolov on word2vec and AI research at Microsoft, Google, Facebook Radim Rehurek 2017
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A friendly introduction to Deep Learning and Neural Networks Luis Serrano 2016
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Introducing tf-seq2seq: An Open Source Sequence-to-Sequence Framework in TensorFlow Anna Goldie, Denny Britz 2017
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Tensorflow Serving by creating and using Docker images Prathamesh Sarang 2017
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BEGAN: STATE OF THE ART GENERATION OF FACES WITH GENERATIVE ADVERSARIAL NETWORKS Loris Felardos 2017
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Understanding the limits of deep learning Mariya Yao 2017
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Five Hundred Deep Learning Papers, Graphviz and Python Daniele Ciriello 2015
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Five Hundred Deep Learning Papers, Part II (Adding JavaScript) Daniele Ciriello 2015
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Practical Neural Networks for NLP Chris Dyer, Yoav Goldberg, Graham Neubig 2016
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On the Expressive Efficiency of Overlapping Architectures of Deep Learning Or Sharir, Amnon Shashua 2017
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Representations for Language: From Word Embeddings to Sentence Meanings Christopher Manning 2017
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Neural Networks for Information Retrieval: Preliminaries Tom Kenter, Maarten de Rijke 2017
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PyData Ann Arbor: Sebastian Raschka | An Introduction to Deep Learning with TensorFlow Sebastian Raschka 2017
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A wizard's guide to Adversarial Autoencoders: Part 3, Disentanglement of style and content. Naresh Nagabushan 2017
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A wizard's guide to Adversarial Autoencoders: Part 4, Classify MNIST using 1000 labels Naresh Nagabushan 2017
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Python gensim Word2Vec tutorial with TensorFlow and Keras Unknown 2017
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Keras Tutorial: Content Based Image Retrieval Using a Convolutional Denoising Autoencoder Adil Baaj 2017
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Build a Recurrent Neural Net in 5 Min Siraj Raval 2017
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Play classic DOS games with your webcam and a neural network Cam Arcade 2017
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Constructing and Evaluating Word Embeddings Marek Rei and Ekaterina Kochmar 2015
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TensorFlow Tutorial #01 Simple Linear Model Havass Laboratories 2016
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Recent Advances in Non-Convex Optimization and its Implications to Learning Anima Anandkumar 2016
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Automating Machine Learning: Advanced WhizzML Workflows Author Unknown 2017
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A Gentle Introduction to Machine Learning Author Unknown 2017
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Neural Network for Machine Learning 2 Jahan, Hryu, Hanbyuly 2017
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Defense Against the Dark Arts: Machine Learning Security and Privacy Ian Goodfellow 2017
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Introduction to Machine Learning Jahan, Hryu, Hanbyuly 2017
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Capturing Dependency Syntax with "Deep" Sequential Models Yoav Goldberg 2017
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image Classification: a core task in Computer Vision Andrej Karpathy & Fei-Fei Li 2016
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Backprop Andrej Karpathy & Fei-Fei Li 2016
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Training Neural Networks Andrej Karpathy & Fei-Fei Li 2016
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Seq2Seq Tutorial Oriol Vinyals And Navdeep Jaitly 2017
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Word Embeddings Explained and Visualized Xin Rong 2017
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Looking for the Missing Signal LÉON BOTTOU 2017
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Efficient Processing of Deep Neural Networks: A Tutorial and Survey Vivienne Sze, Yu-Hsin Chen, Tien-Ju Yang, Joel Emer 2017
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Building Intelligent Systems with Large Scale Deep Learning Jeff Dean 2017
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Machine Learning: The Fundamentals James L. Weaver 2015
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Hardware Architectures for Deep Neural Networks Vivienne Sze, Yu-Hsin Chen, Tien-Ju Yang, Joel Emer 2017
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Neural Text Embeddings for IR Bhaskar Mitra and Nick Craswell 2017
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Challenges for ACL Joakim Nivre 2017
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Overview of PyTorch Adam Paszke, Sam Gross, Soumith Chintala, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Christian Sarofeen, Alban Desmaison, Andreas Kopf 2017
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Pytorch: A framework for new-generation AI Research Adam Paszke, Sam Gross, Soumith Chintala, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Christian Sarofeen, Alban Desmaison, Andreas Kopf 2017
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Pytorch: A framework for new-generation AI Research Adam Paszke, Sam Gross, Soumith Chintala, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Christian Sarofeen, Alban Desmaison, Andreas Kopf 2017
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Seq2Seq tutorial Oriol Vinyals and Navdeep Jaitly 2017
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Tensors Author Unknown 2018
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Interpretable Neural Network Models for Granger Casuality Discovery Emily Fox 2018
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A word is worth a thousand vectors Christopher Moody 2018
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Review of Fundamentals Yoshua Bengio, Olivier Delalleau 2016
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Toward Natural Language Semantics in Learned Representations Sam Bowman 2018
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Deep Goemetric Matrix Completion Federico Monti 2018
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Unraveling the mysteries of stochastic gradient descent on deep neural networks Pratik Chaudhari 2018
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Recurrent Neural Networks Geoff Hinton 2015
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Deep Learning: Approximation of Functions by Composition Zuowei Shen 2018
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LDMNet: Low Dimension Manifold Regularized Neural Networks Wei Zhu 2018
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NLP Demystified Noah Smith 2013
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Natural Language Processing: Algorithms and Applications, Old and New Noah Smith 2015
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Intro to Deep Learning: Supervised Learning Tessa Ferandez 2018
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Modèle : Réseaux à convolution 2 Alexei Nordell Markovits 2018
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Application : Traitement des langues naturelles Arsène Fansi 2018
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Advanced Machine Learning Lecture 4: Deep Learning Essentials Pierre Geurts, Gilles Louppe, Louis Wehenkel 2018
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Deep Learning, Language, and Cognition Christopher Manning 2017
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A Brief Introduction to Deep Learning Yangyan Li 2018
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Debugging the Machine Learning Pipeline Jerry Zhu 2017
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Machine Learning for Dummies Judith Hurwitz, Daniel Kirsch 2018
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Tensor Methods for large-scale Machine Learning Anima Anandkumar 2018
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Capsule Networks Aurélien Géron 2017
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Machine Learning for Systems and Systems in Machine Learning Jeff Dean 2017
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Deep Learning: Practice and Trends Scott Reed, Nando de Freitas, Oriol Vinyals 2017
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The Cost of Calibration Kilian Weinberger 2017
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Differentially Private Machine Learning Kamalika Chaudhuri, Anand D. Sarwate 2017
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Neural Map: Structured Memory for Deep RL Russ Salakhutdinov 2017
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End-to-End Differentiable Proving Tim Rocktasche 2018
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Machine Learning: Generative and Discriminative Models Sargur N. Srihari 2018
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Embeddings, NN, Deep Learning, Distributional Semantics ... in NLP Horacio Rodriguez 2018
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Introduction to Neural Machine Translation Fabienne Cap 2018
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Practical Neural Machine Translation Haddow Sennrich 2017
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Learning to Match for Natural Language Processing and Information Retrieval Hang Li 2012
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Understanding Generative Adversarial Networks Balaji Lakshminarayanan 2018
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CNN insights: What do convolutional neural networks learn about free text? Noel Kennedy 2018
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Distributional compositional semantics in the age of word embeddings: tasks, resources and methodology Anna Rogers, Aleksandr Drozd, Anna Rumshinsky 2018
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Continuous representation of language and its implications Kyunghyun Cho 2018
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An Introduction to Deep Learning for Natural Language Processing Jianfeng Gao 2017
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Affect Detection from Text – from Affect Sciences to Computational Models Alexandra Balahur 2016
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Question Answering with Knowledge Base, Web and Beyond Scott Wen-tau Yih, Hao Ma 2016
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Neural Machine Translation: Basics, Practical Aspects and Recent Trends Fabien Cromieres, Toshiaki Nakazawa, Raj Dabre 2017
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(Deep) Neural Networks for Speech Processing Kate Knill 2015
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Seq2Seq ICML Tutorial Oriol Vinyals, Navdeep Jaitly 2017
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Algorithms that learn to think on their feet John Langford, Hal Daume III 2018
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Continuous representation of language and its implications Kyunghyun Chuo 2018
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Neural Machine Translation and Beyond Kyunghyun Chuo 2018
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Deep Learning for Natural Language Processing Christopher Manning 2018
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Deep Learning of Hierarchical Structure Christopher Manning 2011
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TensorFlow Tutorial Bharath Ramsundar 2018
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Convolutional Neural Networks on Graphs Xavier Bresson 2017
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Deep Learning for Language Understanding Step 1: Word Vectors Christopher Manning 2017
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Intro to Deep Learning Nick Locascio 2017
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Intro to Neural Networks Author Unknown 2018
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Multimodal Learning Victoria Dean 2017
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Scalable Statistical Relational Learning for NLP William Y. Wang, William W. Cohen, Kathryn Rivard Mazaitis 2016
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Scalable Statistical Relational Learning for NLP: Part 2/3 William Y. Wang, William W. Cohen, Kathryn Rivard Mazaitis 2016
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Scalable Statistical Relational Learning for NLP: Part 3/3 William Y. Wang, William W. Cohen, Kathryn Rivard Mazaitis 2016
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Scalable Construction and Reasoning of Massive Knowledge Bases Xiang Ren, Nanyun Peng, William Yang Wang 2018
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Composional Deep Learning Christopher Manning 2015
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Recursive Deep Learning for Modeling Semantic Compositonality Christopher Manning 2013
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Deep Generative Models Ishaan Gulrajani 2017
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Natural Language Inference, Reading Comprehension and Deep Learning Christopher Manning 2016
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Representations for Language: From Word Embeddings to Sentence Meanings Christopher Manning 2017
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Introduction to Machine Learning: Linear Learners Stefan Riezler 2018
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Learning Structured Predictors Xavier Carreras 2016
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Attention and Memory in Deep Learning and NLP Denny Britz 2016
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Introduction to Neural Networks and Deep Learning Dragomir Radev 2017
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Neural Architectures, Training Neural Networks Dragomir Radev 2017
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Word Embeddings Dragomir Radev 2017
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Tools for Deep Learning Dragomir Radev 2017
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Recurrent Neural Networks Dragomir Radev 2017
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Long Short Term Memory Networks Dragomir Radev 2017
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Recursive Neural Networks Dragomir Radev 2017
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Convolutional Neural Networks Dragomir Radev 2017
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Neural Parsing Dragomir Radev 2017
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Neural Machine Translation Dragomir Radev 2017
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Neural Summarization Dragomir Radev 2017
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Neural Question Answering Dragomir Radev 2017
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Neural Generation, Dialogue Systems Dragomir Radev 2017
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Deep Reinforcement Learning Pieter Abbeel 2017
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How to Use Tensorboard (LIVE) Siraj Raval 2017
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Tools for Deep Learning Dragomir Radev 2018
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Long Short Term Memory Networks Dragomir Radev 2018
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Neural Question Answering Dragomir Radev 2018
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Recursive Neural Networks Dragomir Radev 2018
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Neural Architectures, Training Neural Networks Dragomir Radev 2018
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Neural Summarization Dragomir Radev 2018
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Neural Machine Translation Dragomir Radev 2018
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Convolutional Neural Networks Dragomir Radev 2018
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Neural Generation, Dialogue Systems Dragomir Radev 2018
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Neural Parsing Dragomir Radev 2018
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Introduction to Neural Networks and Deep Learning Dragomir Radev 2018
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Recurrent Neural Networks Dragomir Radev 2018
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Word Embeddings Dragomir Radev 2018
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Deep Learning Percy Liang 2017
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Variational Autoencoders David McAllester 2017
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Deep Graphical Models II David McAllester 2017
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Gradients as Dual Vectors David McAllester 2017
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Gated RNNs David McAllester 2017
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Introduction and Historical Notes David McAllester 2017
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Rate-Distortion Autoencoders David McAllester 2017
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Computation Graphs and Backpropagation David McAllester 2017
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Convolutional Neural Networks — CNNs David McAllester 2017
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Deep Reinforcement Learning David McAllester 2017
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Deep Graphical Models I David McAllester 2017
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Memory Networks for Language Understanding Efstratios Gavves 2018
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Exotic Deep Learning Efstratios Gavves 2018
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Learning with neural networks Efstratios Gavves 2018
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Unsupervised, Generative & Adversarial Networks Efstratios Gavves 2018
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Understanding Convnets and Knowledge Transfer Efstratios Gavves 2018
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Recurrent Neural Networks Efstratios Gavves 2018
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Deep Learning & HPC Efstratios Gavves 2018
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Structured Prediction with ConvNets Efstratios Gavves 2018
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Introduction to Neural Networks and Deep Learning Efstratios Gavves 2018
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Convolutional Neural Networks for Computer Vision Efstratios Gavves 2018
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Autoencoder - denoising autoencoder Hugo Larochelle 2017
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Restricted Boltzmann machine Hugo Larochelle 2017
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Training neural networks - activation function derivative Hugo Larochelle 2017
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Sparse coding - dictionary learning algorithm Hugo Larochelle 2017
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Natural language processing - multitask learning Hugo Larochelle 2017
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Autoencoder - linear autoencoder Hugo Larochelle 2017
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Restricted Boltzmann machine - persistent CD Hugo Larochelle 2017
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Computer vision - convolutional network Hugo Larochelle 2017
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Autoencoder - example Hugo Larochelle 2017
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Sparse coding - ZCA preprocessing Hugo Larochelle 2017
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Training neural networks - hidden layer gradient Hugo Larochelle 2017
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Word representations Hugo Larochelle 2017
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Recursive neural network Hugo Larochelle 2017
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Training CRFs - pseudo likelihood Hugo Larochelle 2017
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Feedforward neural network - artificial neural network Hugo Larochelle 2017
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Recursive network training Hugo Larochelle 2017
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Restricted Boltzmann machine - free energy Hugo Larochelle 2017
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Restricted Boltzmann machine - contrastive divergence Hugo Larochelle 2017
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Deep learning - unsupervised pre-training Hugo Larochelle 2017
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Deep learning - deep autoencoder Hugo Larochelle 2017
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Training neural networks - empirical risk minimization Hugo Larochelle 2017
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Deep learning - dropout Hugo Larochelle 2017
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Autoencoders Hugo Larochelle 2017
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Training neural networks - parameter gradient Hugo Larochelle 2017
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Training neural networks - parameter initialization Hugo Larochelle 2017
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Training neural networks Hugo Larochelle 2017
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Feedforward neural network - multilayer neural network Hugo Larochelle 2017
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Training neural networks - regularization Hugo Larochelle 2017
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Autoencoder - loss function Hugo Larochelle 2017
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Sparse coding - definition Hugo Larochelle 2017
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Feedforward neural network - capacity of single neuron Hugo Larochelle 2017
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Neural networks Autoencoder - undercomplete vs. overcomplete hidden layer Hugo Larochelle 2017
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Feedforward neural network Hugo Larochelle 2017
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Feedforward neural network - biological inspiration Hugo Larochelle 2017
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Computer vision - discrete convolution Hugo Larochelle 2017
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language model Hugo Larochelle 2017
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Faster ML Development with TensorFlow Alexander Amini 2018
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Introduction To Deep Learning Alexander Amini 2018
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Deep Learning II Furong Huang 2018
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Neural networks David Sontag 2016
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Neural Networks Ansaf Salleb-Aouissi 2014
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Neural Style Roger Grosse 2018
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Backpropagation Roger Grosse 2018
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Exploding and Vanishing Gradients Roger Grosse 2018
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PCA and Neural Networks Matt Gormley 2016
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Neural Networks and Backpropagation Matt Gormley 2016
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Impact of Deep Learning Maria-Florina Balcan 2015
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Neural Networks, Backpropagation, Recurrent Networks, Convolutional Networks, Deep Belief Networks, Deep Boltzman Machines Maria-Florina Balcan 2015
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EM Algorithm Dan Roth 2018
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CNN and near-diagonalisation Joan Bruna 2016
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Representation of Stationary Process Joan Bruna 2016
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Distributed representations Christopher Manning 2017
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Distributed representations Christopher Manning 2017
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Word Embeddings in Feedforward Networks, Tagging and Dependency Parsing using Feedforward Networks Michael Collins, 2018
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Recurrent Networks, and Attention for Statistical Machine Translation Michael Collins, 2018
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Recurrent Networks, and LSTMs, for NLP Michael Collins, 2018
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Neural Networks in Structured Prediction 2 Chris Dyer 2015
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Neural Networks in Structured Prediction Chris Dyer 2015
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Neural network Jinho D. Choi 2017
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stocastic gradient descent Jinho D. Choi 2017
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LSTM David Bamman 2017
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Deep Learning & Neural Networks Nathan Schneider 2018
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More Word Vectors Richard Socher 2016
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Sequence to Sequence Learning Richard Socher 2016
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Word Window Classification and Neural Networks Richard Socher 2016
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Neural Networks in Speech Recognition Richard Socher 2016
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Wrap up: LSTMs and Recursive Neural Networks Richard Socher 2016
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Project Information Neural Networks & Backprop Richard Socher 2016
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AWS Tutorial Richard Socher 2016
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Convolutional Neural Networks (for NLP) Richard Socher 2016
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Dynamic Memory Networks for Question Answering over Text and Images Richard Socher 2016
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Neural Tips and Tricks Recurrent Neural Networks Richard Socher 2016
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Word Meaning: Distributional Representations and Word Sense Disambiguation Marine Carpuat 2017
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Sequence to Sequence Models for Machine Translation 2 Marine Carpuat 2017
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Sequence to Sequence Models for Machine Translation Marine Carpuat 2017
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Examples of Viterbi, Forward, and Backward Jacob Eisenstein 2014
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Examples of Viterbi, Forward, and Backward Jacob Eisenstein 2014
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Natural Language Processing: A Speech Example Dan Klein 2014
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Natural Language Processing: Machine Translation III Dan Klein 2014
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Natural Language Processing Machine Translation Dan Klein 2014
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Natural Language Processing Machine Translation Dan Klein 2014
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Splitting Words Jason Eisner 2012
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Morphological analysis Tom Kwiatkowski 2016
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Statistical NLP Tom Kwiatkowski 2016
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Lexical Semantics Tom Kwiatkowski 2016
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Recurrent Neural Networks Yoav Artzi 2018
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Lecture 8: Neural Machine TranslaEon Kevin Gimpel 2017
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Lecture 5: Sequence-to-Sequence Modeling and Sentence Embeddings Kevin Gimpel 2017
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Lecture 2: Elements of Neural NLP Kevin Gimpel 2017
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Lecture 9: NMT, finishing up Neural NLP Kevin Gimpel 2017
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Lecture 4: Word Embeddings (2) Kevin Gimpel 2017
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Lecture 1: Introduction Kevin Gimpel 2017
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Lecture 11: Recurrent and Convolutional Neural Networks in NLP Kevin Gimpel 2016
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Lecture 5: Word Vectors Kevin Gimpel 2016
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Lecture 3: Words Kevin Gimpel 2016
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CS11-747 Neural Networks for NLP Convolutional Networks Graham Neubig 2017
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CS11-747 Neural Networks for NLP Recurrent Neural Networks Graham Neubig 2017
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CS11-747 Neural Networks for NLP Models of Words Graham Neubig 2017
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CS11-747 Neural Networks for NLP Multi-task, Multi-lingual Graham Neubig 2017
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CS11-747 Neural Networks for NLP Unsupervised and Semi-supervised Graham Neubig 2017
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CS11-747 Neural Networks for NLP Models of Dialog and Graham Neubig 2017
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CS11-747 Neural Networks for NLP Debugging Neural Networks for NLP Graham Neubig 2017
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CS11-747 Neural Networks for NLP Why is word2vec so fast? Efciency tricks for neural nets Graham Neubig 2017
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CS11-747 Neural Networks for NLP Attention Graham Neubig 2017
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Vector Semantics Dense Vectors Dan Jurafsky 2017
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Vector Semantics Dan Jurafsky 2017
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A SUBJECT OVERVIEW Trevor Cohn 2018
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DISTRIBUTIONAL SEMANTICS Trevor Cohn 2018
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TensorFlow and Deep Learning without a PhD Martin Gorner 2017
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Neural Networks for Machine Learning Geoffrey Hinton 2016
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Mini-Course on Long Short-Term Memory Recurrent Neural Networks with Keras Jason Brownlee 2017
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Beyond Seq2Seq with Augmented RNNs Edward Grefenstette 2016
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Information Theory of Deep Learning Naftali Tishby 2017
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Deeplearning.ai Author Unknown 2017
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CMU Neural Nets for NLP 2017 Graham Neubig 2017
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Improving Deep Neural Networks: Hyperparameter Author Unknown 2017
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Introduction to TensorFlow Chris Manning, Richard Socher 2017
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Million Song Dataset Challenge Author Unknown 2011
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Tensorflow for Deep Learning Research - Lecture 1 Labhesh Patel 2017
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Applied Deep Learning - Part 1: Artificial Neural Networks Arden Dertat 2017
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Applied Deep Learning - Part 2: Real World Case Studies Arden Dertat 2017
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But what *is* a Neural Network | Deep learning, Part 1 3Blue1Brown 2017
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Analyzing the Meaning of Sentences Steven Bird, Ewan Klein, Edward Loper 2014
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Deep Learning: Theory, Algorithms, and Applications Author Unknown 2017
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Artificial Neural Networks with Python - 1 - Introduction Cristi Vlad 2017
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NIPS 2016 Spotlight Videos NIPS Conference 2016
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Deep Learning Book Part 1 Alena Kruchkova 2017
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CMU Neural Nets for NLP 2017(9): Attention Graham Neubig 2017
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Artificial Neural Networks with Python - 5 - Single Layer Neural Net Cristi Vlad 2017
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PyTorch Lecture 01: Overview Sung Kim 2017
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A Step by Step Introduction to Deep Learning with Python: Day 1 - What is Deep Learning? Machine Learning TV 2017
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Deepschool.io Sachinthaka R. Abeywardana 2017
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Stanford Tensorflow Tutorials Huyen Nguyen 2017
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Network Science Albert-Laszlo Barabasi 2015
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Natural Language Processing with Representation Learning Samuel Bowman and Kyunghyun Cho 2017
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CS224N Midterm Review Nishith Khandwala, Barak Oshri, Lisa Wang, Juhi Naik 2017
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Two Ways to Implement LSTM Network using Python – with TensorFlow and Keras rubikscode 2018
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Introduction to Convolutional Neural Networks rubikscode 2018
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Understanding Long Short-Term Memory Networks (LSTMs) rubikscode 2018
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Common Neural Network Activation Functions rubikscode 2017
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Introduction to TensorFlow – With Python Example rubikscode 2018
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Applications of Deep Neural Networks Jeff Heaton 2018
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DeepLearning.TV Author Unknown 2015
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Automatic Generation of Story Highlights Data Set Kristian Woodsend, Mirella Lapata 2010
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Downsampled ImageNet Aaron van den Oord, Nal Kalchbrenner, and Koray Kavukcuoglu 2016
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Word Vectors Manaal Faruqui, Chris Dyer 2016
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Addressee and Response Selection Task Hiroki Ouchi, Yuta Tsuboi 2016
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A Reading Comprehension Dataset for the Artificial Intelligence research community Tri Nguyen, Mir Rosenberg, Xia Song, Jianfeng Gao, Saurabh Tiwary, Rangan Majumder and Li Deng 2017
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WikiTableQuestions: a Complex Real-World Question Understanding Dataset Ice Pasupat 2016
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The 6th Open Challenge on Question Answering Over Linked Data Christina Unger 2016
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theanets Leif Johnson 2017
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RNNLG Shawn Wen 2016
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Zoph_RNN: A C++/CUDA toolkit for training sequence and sequence-to-sequence models across multiple GPUs Xing Shi 2017
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Stack RNN Armand Joulin, Tomas Mikolov 2015
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SyntaxNet: Neural Models of Syntax Tensorflow 2017
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SkFlow TensorFlow 2016
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TensorFlow Tutorials Parag K Mital 2017
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Neural Language Model Joseph Turian 2010
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Sequence-to-Sequence Learning with Attentional Neural Networks Guillaume Klein 2016
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Sequence to Sequence Learning with Keras Fariz Rahman 2015
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Visual Analysis for State Changes in RNNs Sebastian Gerhrmann, Hendrik Strobelt, Bernd Huber, Hanspeter Pfister, Alexander M. Rush 2016
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Long Short Term Memory Units Wojciech Zaremba 2015
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Tree-Structured Long Short-Term Memory Networks Kai Sheng Tai, Richard Socher, Christopher D. Manning 2015
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PathLSTM Michael Roth, Mirella Lapata 2017
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Top-down Tree LSTM Xingxing Zhang, Liang Lu, Mirella Lapata 2016
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Recurrent Neural Network Tutorial Denny Brtiz 2015
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Word Embedding Visual Inspector Xin Rong 2015
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Eigenwords Resource Page Lyle Ungar 2012
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Attention-Based Summarization Alexander M. Rush, Sumit Chopra, Jason Weston 2015
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A Convolutional Attention Network for Extreme Summarization of Source Code Ehud Ben-Reuven, Miltos Mallamanis 2016
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Attention-Based Summarization Harvard NLP 2015
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Attention-Based Summarization Taehoon Kim 2016
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Keras: Deep Learning library for TensorFlow and Theano Francois Chollet 2017
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Keras Documentation Francois Chollet 2017
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Keras Example: LSTM on the IMDB sentiment classification task Francois Chollet 2017
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word2parvec Oren Melamud, Ido Dagan, Jacob Goldberger 2015
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Blocks Example - Machine Translation Bart van Merriënboer, Dzmitry Bahdanau, Vincent Dumoulin, Dmitriy Serdyuk, David Warde-Farley, Jan Chorowski, Yoshua Bengio 2015
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Effective Approaches to Attention-based Neural Machine Translation Thang Luong, Hieu Pham, Christopher Manning 2015
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Question Answering Neural Network with Trans-Sentential Averaging John Co-Reyes 2014
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ConvNetJS Andrej Karpathy 2015
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Multi-Perspective Convolutional Neural Networks for Modeling Textual Similarity hohoCode 2017
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Convolutional Neural Network for Text Classicaition in TensorFlow Denny Britz 2015
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Convolutional Neural Networks for Sentence Classification Yoon Kim 2016
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Caffe: Deep learning framework in Python and Matlab Yangqing Jia and Evan Shelhamer 2017
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Character-Aware Neural Language Models Yoon Kim, Yacine Jernite, David Sontag, and Alexander M. Rush 2016
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Implementing a Neural Network from Scratch Denny Britz 2015
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RNN/LSTM auto encoder with sequence learning approaches sq6ra 2016
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DeepLearning4j: Deep learning framework in Java Alex Black, Suneel Marthi, Kai Sasake, Taisuke Oe, Jeffrey Tang, Melanie Warrick, and Eron Wright 2017
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Automatically generate headlines to short articles Ehud Ben-Reuven 2017
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NNBlocks Frederico Tommasi Caroli 2016
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Datasets Caglar Gulcehre 2017
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The Microsoft Cognitive Toolkit Microsoft 2017
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mxnet: A Flexible and Efficient Library for Deep Learning Tianqi Chen, Mu Li, and many others 2017
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MultiVec: C++ implementation of word2vec, bivec, and paragraph vector. Alexandre Bérard, Jérémy Ferrero, Christophe Servan, Mats Byrkjeland 2015
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Simple, Strong Deep-Learning Baselines for NLP in several frameworks Dan Pressel 2016
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fastText Edouard Grave, Piotr Bojanowski, Armand Joulin 2016
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Easy to Learn and Use Distributed Deep Learning Platform Yu Yang, Gang Liao, Tao Luo, Jacques Qiao 2016
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The Microsoft Cognitive Toolkit Frank Seide, Willi Richert, Amit Agarwal, and others 2014
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Neural Coref Models Sam Wiseman, Alexander M. Rush, Stuart M. Shieber 2015
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Learning to Execute Abhi Agg, Wojciech Zaremba 2014
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Towards Universal Paraphrastic Sentence Embeddings code John Wieting, Mohit Bansal, Kevin Gimpel, Karen Livescu 2016
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neon Intel Nervana 2017
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Awesome MXNet Distributed (Deep) Machine Learning Community 2017
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Hierarchical Encoder Decoder RNN (HRED) with Truncated Backpropagation Through Time (Truncated BPTT) Iulian Vlad Serban and Alessandro Sordoni 2017
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lang2logic Li Dong 2017
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PaddlePaddle (PArallel Distributed Deep LEarning) Yu Yang, Gang Liao, Tao Luo 2016
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RNNLIB Alex Graves 2013
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Wiki2Vec David Przybilla 2015
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translit-rnn: Automatic transliteration with LSTM Tigran Galstyan, Hrayr Harutyunyan, Hrant Khachatrian, Karen Hambardzumyan, Arman Yeghiazaryan 2016
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Convolutional Attention Network Ehud Ben-Reuven, Miltos Mallamanis 2016
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Addressee and Response Selection System Hiroki Ouchi, Yuta Tsuboi 2016
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TheanoLM Seppo Enarvi 2017
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Kyunghyun Cho's software Kyunghyun Cho 2017
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Blocks LISA Lab 2015
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DeepWalk Bryan Perozzi, Rami Al-Rfou, Haochen Chen 2014
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TFLearn: Deep learning library featuring a higher-level API for TensorFlow. Aymeric Damien, Will Ballard, ichuang, Burness Duan 2016
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TensorFlow With The Latest Papers Implemented Nick Shah, Ofir Press 2016
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NLP_from_scratch Lajanugen Logeswaran 2015
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nmtpy Ozan Ça?layan, Loic Barrault 2016
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TensorFlow Fold Moshe Looks, DeLesley Hutchins 2017
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Stack-augmented Parser-Interpreter Neural Network Samuel R. Bowman, Jon Gauthier, Abhinav Rastogi, Raghav Gupta, Christopher D. Manning, Christopher Potts 2016
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DeepMind Lab Thomas Köppe, Jithin Odattu 2016
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Contextual RNN-GANs for Abstract Reasoning Diagram Generation: code Arnab Ghosh, Viveka Kulharia, Amitabha Mukerjee, Vinay Namboodiri, Mohit Bansal 2016
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DyNet: The Dynamic Neural Network Toolkit Graham Neubig, Chris Dyer, Yoav Goldberg, Austin Matthews, Waleed Ammar, Antonios Anastasopoulos, Miguel Ballesteros, David Chiang, Daniel Clothiaux, Trevor Cohn, Kevin Duh, Manaal Faruqui, Cynthia Ga 2017
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Dialog-based Language Learning Jiwei Li 2016
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Neural Programmer Arvind Neelakantan, Quoc V. Le, Mart´?n Abadi, Andrew McCallum, Dario Amodei 2017
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AutoExtend - Extending Word Embeddings to Embeddings for Synsets and Lexeme Sascha Rothe, Hinrich Schutze 2015
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seq2seq Anna Goldie, Denny Britz 2017
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TensorFlow Models TensorFlow Team 2016
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bulbea Achilles Rasquinha 2017
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Charagram: Embedding Words and Sentences via Character n-grams John Wieting 2016
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Lasagne Jan Schlüter, Sander Dieleman, Colin Raffel, Eben Olson, Søren Kaae Sønderby, Daniel Nouri 2014
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learn2sum Chris Kedzie 2016
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Temporal Summarization Chris Kedzie 2016
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jacana Xuchen Yao, Benjamin Van Durme and Peter Clark 2013
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Keraflow: Deep Learning library for Theano and Tensorflow. Keras follower Shih-Ming Wang 2016
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CodaLab Workshets Eric Carmichael, Max Wang 2017
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Breeze David Hall 2009
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Reasoning About Pragmatics with Neural Listeners Speakers Jacob Andreas, Dan Klein 2016
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gplearn Trevor Stephens 2015
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Deep learning in Python Anders Boesen Lindbo Larsen, Lasse Reedtz 2014
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MXNet Tianqi Chen, Mu Li, Eric Junyuan Xie, Bing Xu, Chiyuan Zhang, Yizhi Liu, Tianjun Xiao, Yutian Li, Yuan (Terry) Tang, Hu Shiwen, Qiang Kou (KK), Xingjian Shi, Yao Wang, Sandeep Krishnamurthy, Chuntao H 2015
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CMUSphinx Tutorial For Developers Alex Rudnicky, Alan W. Black, Bhiksha Raj, David Huggins-Daines, Evandro B. Gouvea, Kevin A. Lenzo, Nickolay V. Shmyrev,Peter Wolf, Apurv Tiwari,Cosmin Boaca,Eric H. Thayer ,Arseniy Gorin, Holger Bran 2017
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Rasa NLU Alan Nichol, Tom Bocklish, Alexander Weidauer, Giovanni Iovino, Nick Pawlowski 2017
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Five Hundred Deep Learning Papers Daniele Ciriello 2015
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Code samples for "Neural Networks and Deep Learning" Michael Nielsen 2012
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TRAIN FASTER-RCNN ON A NEW DATASET Ross Girshick, Xin Lei Pan 2015
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ParlAI FAIR 2017
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Pyevolve Christian S. Perone, Amit Saha 2010
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Breze Justin Bayer, Sebastian Urban, Adrià Puigdomènech 2012
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Get To The Point: Summarization with Pointer-Generator Networks Abi See 2017
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Sequence-to-Sequence with Attention Model for Text Summarization Xin Pan, Peter Liu 2016
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Fully Character-Level Neural Machine Translation Jason Lee, Kyunghyun Cho 2016
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ProPPR: Programming with Personalized PageRank William Yang Wang, Kathryn Mazaitis, William W. Cohen 2016
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Review Network for Caption Generation Zhilin Yang, Ye Yuan, Yuexin Wu, Ruslan Salakhutdinov, William W. Cohen 2016
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pixel-cnn++ Tim Salimans, Andrej Karpathy, Xi Chen, Diederik P. Kingma, and Yaroslav Bulatov 2017
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Graph Convolutional Networks Thomas N. Kipf, Max Welling 2017
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Practical PyTorch: Translation with a Sequence to Sequence Network and Attention Sean Robertson 2017
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The Predictron Zhongwen Xu 2016
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PyTorch Adam Paszke, Sam Gross and Soumith Chintala 2012
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Announcing TensorFlow Fold: Deep Learning With Dynamic Computation Graphs Moshe Looks, Marcello Herreshoff, DeLesley Hutchins 2017
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OpenNMT Guillaume Klein, Yoon Kim, Yuntian Deng, Jean Senellart, Alexander M. Rush 2017
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Machine Learning with TensorFlow: code Nishant Shukla 2017
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Machine Learning with TensorFlow Nishant Shukla 2017
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Tensor network machine learning Miles Emstoudenmire 2016
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CNTK Venelin Valkov 2015
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Google Summer of Code 2017 – Week 1 of Integrating Gensim with scikit-learn and Keras Chinmaya Pancholi 2017
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NSynth: Neural Audio Synthesis Jesse Engel, Cinjon Resnick, Adam Roberts, Sander Dieleman, Karen Simonyan, Mohammad Norouzi, Doug Eck 2017
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Sonnet Diego Couto de Las Casas 2017
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Microsoft Updates its Deep Learning Toolkit Chris Basoglu 2017
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BIST Parsers Eliyahu Kiperwasser 2017
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Easy-first Parser Eliyahu Kiperwasser 2016
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Open AI Gym Open AI 2017
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Stanford NLP Group Software Stanford NLP Group 2017
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Differentiable Neural Computer (DNC) Jason Ramapuram 2016
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neuro-lab Nuel Ezenwere 2017
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Caffe2 Facebook Open Source 2017
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nolearn: scikit-learn compatible neural network library Daniel Nouri 2014
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deepnet: Implementation of some deep learning algorithms Nitish Srivastava 2012
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Convolutional Neural Networks for Matlab for classification and segmentation Sergey Demyanov 2013
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Reproducing Chen & Manning (2014) Minh Le 2017
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Learning to Learn in TensorFlow Sergio Gómez 2016
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BEGAN: Boundary Equilibrium Generative Adversarial Networks Heumi 2017
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Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet, Inception, SqueezeNet) Aaron Chen 2017
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RocAlphaGo wrongu, Tyler Trine, James Tauber, Louis Marti, Thouis (Ray) Jones 2016
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neural image analogies Adam Wentz 2016
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Kur: Descriptive Deep Learning Adam Sypniewski, Noah Shutty 2016
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TensorLayer Data Science Institute, Imperial College London 2017
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TensorFlow Examples Aymeric Damien, Norman Heckscher 2017
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Neural Doodle Alex J. Champandard, Jared Feng 2017
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neural-storyteller Ryan Kiros, Yukun Zhu, Ruslan Salakhutdinov, Richard S. Zemel, Antonio Torralba, Raquel Urtasun, and Sanja Fidler 2015
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Theano-Tutorials Alec Radford 2014
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neural-style Justin Johnson, Shubhanshu Mishra 2014
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deepdream Alexander Mordvintsev, Michael Tyka, Christopher Olah 2015
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Pylearn2: A machine learning research library Ian J. Goodfellow, David Warde-Farley, Pascal Lamblin, Vincent Dumoulin, Mehdi Mirza, Razvan Pascanu, James Bergstra, Frédéric Bastien, and Yoshua Bengio 2016
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scikit-neuralnetwork Alex J. Champandard 2015
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Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks Alec Radford, Luke Metz, Soumith Chintala 2015
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Sockeye Tobias Domhan, Kellen Sunderland 2017
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Sort-of-CLEVR Kim Heecheol 2017
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Learning a Neural Semantic Parser with User Feedback Srinivasan Iyer 2017
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Facebook AI Research Sequence-to-Sequence Toolkit FAIR 2017
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parlai 0.1.0 Alexander H Miller 2017
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Code, exercises and solutions for popular Reinforcement Learning algorithms Denny Britz 2016
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NeuralTalk2 Andrej Karpathy, Justin Johnson 2015
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char-rnn Andrej Karpathy 2014
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Neural network visualization toolkit for keras Raghavendra Kotikalapudi 2016
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Neural Network Libraries by Sony Sony 2017
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Code examples for the course CS 20SI: TensorFlow for Deep Learning Research Chip Huyen 2016
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BioPy David Cunningham, Jared M. Smith 2015
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Deep learning made easy Zygmunt Zaj?c 2013
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Generative Models Agustinus Kristiadi 2016
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Neural Dialogue Generation Jiwei Li 2017
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Text To Image Synthesis Using Thought Vectors Paarth Neekhara, Neil Halelamien 2016
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Deep Learning with PaddlePaddle Gang Liao, Tao Luo, Gong Wei Bao, qingqing01, Yiwang baidu, Yu Yang, Cao Ying 2016
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Neural Machine Translation Implementations Jon Safari 2016
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SGNMT Felix Stahlberg, Eva Hasler, Aurelien Waite, Bill Byrne 2016
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Automatic Summarisation of Scientific Papers Ed Collins, Isabelle Augenstein, Sebastian Riedel 2017
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lamtram: A toolkit for language and translation modeling using neural networks Graham Neubig, Michael Denkowski, Hieu Hoang 2017
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Tensorflow tutorial on convolutional neural networks Cole Murray 2017
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deepmark Soumith Chintala 2016
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Deep Reinforcement Learning in TensorFlow Taehoon Kim 2017
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DarkForest, the Facebook Go engine Facebook Research 2017
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Fast Recurrent Networks Library Greg Diamos 2016
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Introducing Cloud Natural Language API, Speech API open beta and our West Coast region expansion Apoorv Saxena 2016
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A Large-Scale Video Benchmark for Human Activity Understanding Fabian Caba Heilbron, Victor Escorcia, Bernard Ghanem, Juan Carlos Niebles 2015
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neocortex.js Leon Chen 2016
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Neural Style Transfer & Neural Doodles Somshubra Majumdar 2017
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Mindpark Danijar Hafner 2017
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Aligning the fastText vectors of 78 languages Nils Hammerla 2017
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Wasserstein GAN Martin Arjovsky, Soumith Chintala, Léon Bottou 2017
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Introducing Keras 2 Francois Chollet 2017
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pix2pix Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, Alexei A. Efros 2017
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Code for Translation with a Sequence to Sequence Network and Attention Tutorial Sean Robertson 2017
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iPython Noetbook for Translation with a Sequence to Sequence Network and Attention Tutorial Sean Robertson 2017
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Classifying Names with a Character-Level RNN: Code Sean Robertson 2017
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Classifying Names with a Character-Level RNN: iPython Notebook Sean Robertson 2017
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Recurrent Additive Networks Kenton Lee, Omer Levy, Luke Zettlemoyer 2017
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Classifying-Earthquakes David Clark 2016
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Pyevolve Christian S. Perone 2009
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eval-word-vectors Manaal Faruqui 2014
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InferSent Alex Conneau 2017
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Neural Turing Machine in Tensorflow Taehoon Kim 2015
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End-To-End Memory Networks in Tensorflow Taehoon Kim 2015
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Word2Vec in Tensorflow Taehoon Kim 2015
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LSTMs for Human Activity Recognition Guillaume Chevalier 2017
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DeepQA Matt Gardner, Pradeep Dasigi, Nelson Liu, Mark Neumann, Johannes Welbl 2015
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Bi-directional Attention Flow for Machine Comprehension Minjoon Seo 2016
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Seq2seq Chatbot for Keras Oswaldo Ludwig 2017
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Show, Attend and Tell yunjey 2016
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Shakespeare translations using TensorFlow Motoki Wu 2015
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Deep Q&A Etienne Pot, Laurent Eschenauer 2015
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Neural Caption Generator with Attention Taeksoo Kim 2015
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Character-Aware Neural Language Models Taehoon Kim 2015
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TFLearn: Deep learning library featuring a higher-level API for TensorFlow Aymeric Damien 2016
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Convolutional Neural Network demo Siraj Raval 2017
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T2T: Tensor2Tensor Transformers Ryan Sepassi, Lukasz Kaiser 2017
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Implementation of Skip-Thought Vectors Chris Shallue 2017
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NEMATUS: Attention-based encoder-decoder model for neural machine translation Rico Sennrich 2015
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Neural Monkey: Neural Sequence Learning Using TensorFlow Jindra Helcl, Jindrich Libovicky 2016
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Memory-Augmented Neural Networks Alexander Miller 2015
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code for the paper "Improved Techniques for Training GANs" Tim Salimans, Ian Goodfellow, Wojciech Zaremba 2017
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Crypto-RNN: Decoding Polyalphabetic Ciphers with Recurrent Neural Networks Sam Greydanus 2017
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Simple and Efficient Learning with Dynamic Neural Networks Graham Neubig 2017
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Visual Interaction Networks Jaesik Yoon 2017
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DrQA Adam Fisch 2017
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Amazon DSSTNE: Deep Scalable Sparse Tensor Network Engine Rejith Joseph, Tristan Penman, rybakov, scottlegrand 2017
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Tensorflow tutorial Manjunath Kudlur 2016
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Implementation of Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank Hyun Oh Song 2015
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SentEval D. Kiela, A. Conneau, A. Jabri, M. Nickel 2017
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Perceptron Caspar Wylie 2017
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Neural Model for converting Image-to-Markup Yuntian Deng 2017
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Sentence Convolution Code in Torch Yoon Kim 2017
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Morphological Word Embeddings Ryan Cotterell, Hinrich Schutze 2017
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TensorSlow Author Unknown 2017
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VectorFlow Netflix 2017
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TensorFire Kevin Kwok, Guillermo Webster, Anish Athalye, and Logan Engstrom. 2017
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deeplearn.js Nikhil Thorat, Daniel Smilkov and Charles Nicholson. 2017
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text2vec Nikhil Thorat, Daniel Smilkov and Charles Nicholson. 2017
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Foolbox Jonas Rauber & Wieland Brendel 2017
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AWD-LSTM Language Model Salesforce 2017
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Sketch-RNN: A Generative Model for Vector Drawings Google 2017
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Neural Monkey documentation Jind?ich Libovický, Jind?ich Helcl, Tomáš Musil 2017
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The Neural Turing Machine Author Unknown 2017
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Tensorflow Generative Model Collections Author Unknown 2017
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Attention Sum Reader Rudolf Kadlec, Martin Schmid, Ondrej Bajgar, Tamir Klinger, Ladislav Kunc, Jan Kleindienst 2017
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Datasets for Data Science and Machine Learning Author Unknown 2017
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#MSR RastRDFStore Package Author Unknown 2017
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GraphQuestions: A Characteristic-rich Question Answering Dataset Yu Su, Huan Sun, Brian Sadler, Mudhakar Srivatsa, Izzeddin Gur, Zenghui Yan, and Xifeng Yan 2017
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Allen NLP The Allen Institute for Artificial Intelligence 2017
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Tesseract OCR Author Unknown 2017
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Asynchronous RL in TensorFlow + Keras + OpenAI's Gym Author Unknown 2017
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Simple DQN Author Unknown 2017
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Taxi-v1 T Erez, Y Tassa, E Todorov 2017
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word2vec-recommender Manas Ranjan Kar, Akhil Gupta 2017
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Tensorflow Implementation of Recursive Neural Networks Kai Sheng Tai, Richard Socher, and Christopher D. Manning 2017
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Stanza Author Unknown 2017
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Pytorch Generative Model Collections Hwalsuk Lee 2017
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Song Lyrics Generator Author Unknown 2017
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Pix2code Author Unknown 2017
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Facebook AI Research Sequence-to-Sequence Toolkit (pyTorch version) Facebook Research 2017
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DataVec Deeplearning4j 2017
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Deep Server puyash 2017
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Sequence to Sequence Trasnduction with Hard Monotonic Attention Roee Aharoni, Yoav Goldberg 2016
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Million Song Dataset Thierry Bertin-Mahieux, Daniel P.W. Ellis, Brian Whitman, and Paul Lamere 2011
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FigureQA Author Unknown 2017
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Fabrik Author Unknown 2017
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Relation Classification using LSTMs on Sequences and Tree Structures Author Unknown 2017
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DeepL Author Unknown 2017
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Datasets for Natural Language Processing Kyubyong 2017
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Can Convolutional Neural Networks Crack Sudoku Puzzles? Kyubyong 2017
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Pre-Trained Word Vectors of 30+ languages Kyubyong 2017
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TensorFlow Exercises Kyubyong 2017
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A (Heavily Documented) TensorFlow Implementation of Tacotron: A Fully End-to-End Text-To-Speech Synthesis Model Kyubyong 2017
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A TensorFlow Implementation of the Transformer: Attention Is All You Need Kyubyong 2017
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Practical PyTorch Kyubyong 2017
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Rubiks Cube Convnet Author Unknown 2017
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Textblob: Simple, Pythonic, text processing Steven Loria 2017
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PDFAnno: Tools to annotate PDFs in the browser Paper AI 2017
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Implementation of skip-thought vectors in Tensorflow Dmitry Persiyanov 2017
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CogComp-NLPy CogComp 2017
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Persontyle Workshop for Applied Deep Learning Amaia Salvador and Santiago Pascual 2017
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LF-LDA and LF-DMM: Improving Topic Models with Word Embeddings Dat Quoc Nguyen, Richard Billingsley, Lan Du and Mark Johnson 2017
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Colibri Core Maarten van Gompel 2017
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Recurrent Convolutional Neural Network Text Classifier Michael A. Alcorn 2017
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Paragraph Vectors Nejc Ilenic 2017
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monkeylearn-python Monkeylearn 2017
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Seq2Seq Chatbot Author Unknown 2017
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Paraphrase ID TensorFlow Nelson Liu, Omar Khan 2017
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Dynamic Memory Networks in TensorFlow Author Unknown 2017
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MemN2N: End-To-End Memory Network using TensorFlow Author Unknown 2017
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Zemberek-NLP Ahmet Afsin Akin, Mehmet Dundar Akin 2017
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Thinc: Practical Machine Learning for NLP in Python Matthew Honnibal 2016
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Attention is all you need: A Pytorch Implementation Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, Illia Polosukhin, arxiv 2017
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NeuroNER Franck Dernoncourt, Ji Young Lee, Ozlem Uzuner, Peter Szolovits 2016
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Python impl for TextRank Rada Mihalcea 2016
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KoNLPy Steven Han 2017
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displaCy.js: An open-source NLP visualiser for the modern web Author Unknown 2017
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Flickr Personal Taxonomies Author Unknown 2011
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PyTorch Implementation of the Coupled GAN Algorithm for Unsurpervised Image-to-Image Translation Ming-Yu Liu, Thomas Breuel, Jan Kautz 2017
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PySC2 - StarCraft II Learning Environment Author Unknown 2017
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Pyfasttext Author Unknown 2017
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LeNet-5, convolutional neural networks Author Unknown 2017
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ZhuSuan Author Unknown 2017
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Graph ConvNets in PyTorch Xavier Bresson 2017
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Permance RNN Author Unknown 2017
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RecurrentJS MIT 2017
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t-SNE running on 50-dimensional word vectors Andrej Karpathy 2017
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Neural Networks demo in Javascript Andrej Karpathy 2017
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Awesome NLP Resources for Hungarian Gyorgy Orosz 2017
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Vowpal Wabbit John Langford 2017
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A Python Wrapper for Google SyntaxNet Ping Chu Hung 2017
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Word2Vec Tomas Mikolov, Quoc V. Le, Ilya Sutskever 2017
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Tools for Natural Language Analysis Miguel Ballesteros, Bernd Bohnet 2014
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Neural Dep Srl Marcheggiani, Anton Fr 2017
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Groningen Meaning Bank (GMB) Johan Bos 2017
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The Gluon API Specification Gluon-API 2017
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Character-level text classification puyash 2017
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Question-Answer Dataset Noah A. Smith, Michael Heilman, Rebecca Hwa 2013
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DyNet implementation of stack LSTM experiments by Grefenstette et al. Brian DuSell 2017
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Potara: Multi-document summarization tool sildar 2015
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Lime: Explaining the predictions of any machine learning classifier Marco Tulio Correia Ribeiro 2017
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Distraction-based Neural Models for Document Summarization Qian Chen, Xiaodan Zhu, Zhenhua Ling, Si Wei, Hui Jiang 2017
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Enhanced LTSM for natural language inference Qian Chen, Xiaodan Zhu, Zhenhua Ling, Si Wei, Hui Jiang, Diana Inkpen 2017
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RaSoR: Learning Recurrent Span Representations for Extractive Question Answering Shimi Salant 2017
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Word Vector Evaluation Manaal Faruqui, Chris Dyer 2014
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Multimodal Information Group Tools Mark Przybocki 2017
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Word Embeddings Rami Al-Rfou, Bryan Perozzi, Steven Skiena 2013
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Word Vectors Upload Author Unknown 2017
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Retrofitting Manaal Faruqui 2017
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Incremental Word2Vec Wammar 2017
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MegaFace and MF2: Million-Scale Face Recognition Ira Kemelmacher-Shlizerman 2015
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Tensorflow Seq2seq Text Summarization Tsinghua University 2017
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Tensorflow NRE Tsinghua University 2017
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thunlp/paragraph2vec Tsinghua University 2017
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Transforming-Autoencoder-TF Nikhil Mehta 2017
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Quasi-Recurrent Neural Network (QRNN) for PyTorch Salesforce 2017
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Companion Jupyter notebooks for the book "Deep Learning with Python" Fchollet 2017
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Artificial Neural Networks in Python Cristi Vlad 2017
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DeepChem Peter Eastman, Evan Feinberg, Joe Gomes, Karl Leswing, Vijay Pande, Aneesh Pappu, Bharath Ramsundar, Michael Wu 2017
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SWI Prolog Jan Wielemaker 2017
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LabelImg Darren Lo 2017
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TensorFlow Lattice: Lattice modeling in TensorFlow Authors Unknown 2017
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tree_rnn ofirnachum 2017
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TellinaTool/awesome_nmt Tellina 2017
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Tree2Seq: Tree-to-Sequence Attentional Neural Machine Translation Author Unknown 2017
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Awesome Neural Machine Translation Tellina 2017
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Tellina Tellina 2017
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Success with Style: Using Writing Style to Predict the Success of Novels. Vikas Ashok, Song Feng, and Yejin Choi 2013
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Code for “Graph degeneracy and submodularity for unsupervised extractive summarization” Antoine J.-P. Tixier, Polykarpos Meladianos, Michalis Vazirgiannis 2017
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End-to-end Neural Coreference Resolution Kenton Lee 2017
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awesome-question-answering Apurv Verma 2017
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Representation Learning: A Review and New Perspectives Yoshua Bengio, Aaron Courville, Pascal Vincent 2014
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Deep Learning, NLP, and Representations Christopher Olah 2014
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Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python Sebastian Raschka 2016
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Deep Learnnig at Oxford 2015 Nando de Freitas 2015
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Long Short-Term Memory Over Recursive Structures Xiaodan Zhu, Parinaz Sobhani, Hongyu Guo 2017
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CS 224D: Deep Learning for NLP, Lecture Notes 1 Francois Chaubard, Rohit Mundra, Richard Socher 2015
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CS 224D: Deep Learning for NLP, Lecture Notes 2 Francois Chaubard, Rohit Mundra, Richard Socher 2015
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CS 224D: Deep Learning for NLP, Lecture Notes 5 Francois Chaubard, Rohit Mundra, Richard Socher 2015
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A Statistical View of Deep Learning Shakir Mohamed 2015
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Deep Learning: An Introduction for Applied Mathematicians Catherine F. Higham, Desmond J. Higham 2018
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Natural Language Processing Jacob Eisenstein 2018
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Deep Learning Ian Goodfellow and Yoshua Bengio and Aaron Courville 2016
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Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation Albert Gatt, Emiel Krahmer 2018
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A Brief Introduction to Neural Networks David Kriesel 2018
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Nothing but Net(works) Tom McCoy 2017
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Theano Exercises Ian Goodfellow 2015
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Awesome Recurrent Neural Networks Myungsub Choi, Taeksoo Kim, Jiwon Kim 2017
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A Neural Network for Machine Translation, at Production Scale Quoc V. Le, Mike Schuster 2016
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Zero-Shot Translation with Google's Multilingual Neural Machine Translation System Mike Schuster, Melvin Johnson, Nikhil Thorat 2016
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IFT6266 – H2015 Representation Learning. A mostly deep learning course. Aaron Courville 2015
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Deep Learning; Software Links Caglar Gulcehre 2006
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A Neural Network For Factoid Question Answering Over Paragraphs Mohit Iyyer, Jordan Boyd-Graber, Leonardo Claudino, Richard Socher, and Hal Daume III 2014
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Some starting points for deep learning and RNNs Deniz Yuret 2014
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Deep Learning for NLP at Oxford with Deep Mind 2017 Zafarullah Mahmood 2017
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Machine Learning Oxford Course Nando de Freitas 2014
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CS231n: Assignment 3 Andrej Karpathy 2016
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Some New Interesting Deep Learning Datasets for Data Scientists Muktabh Mayank 2017
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Dynamic Pooling And Unfolding Recursive Autoencoders For Paraphrase Detection Richard Socher, Eric H. Huang, Jeffrey Pennington, Andrew Y. Ng, Christopher D. Manning 2011
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KDD Panel: Is Deep Learning the New 42? Pedro Domingos, Nando de Freitas, Isabelle Guyon, Jitendra Malik, Jennifer Neville, Andrei Broder 2016
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Yann LeCun - Deep Learning and the Future of AI Yann LeCun 2017
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Top 5 arXiv Deep Learning Papers, Explained Matthew Mayo 2015
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UCL Course on RL David Silver 2015
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10 Days of Deep Learning Vaibhav Srivastav 2017
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Google Text Normalization Challenge Google Natural Language Understanding Research 2017
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Open Practical Chris Dyer, Phil Blunsom, Yannis Assael, Brendan Shillingford, Yishu Miao, Jan Buys 2017
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Practical 1: word2vec Brendan Shillingford, Yannis Assael, Chris Dyer 2017
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Practical 2: Text Classification Chris Dyer, Yannis Assael, Brendan Shillingford 2017
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Practical 3: Text Classification with RNNs Chris Dyer, Phil Blunsom, Yannis Assael, Brendan Shillingford, Yishu Miao 2017
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Sempre Viewer Ice Pasupat 2016
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Microsoft launches open-source Cognitive Toolkit 2.0 Vishakha Jha 2017
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The RepEval 2017 Shared Task Sam Bowman, Yoav Goldberg, Felix Hill, Angeliki Lazaridou, Omer Levy, Roi Reichart, Anders Sogaard 2017
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Try Deep Learning in Python now with a fully pre-configured VM Adam Geitgey 2017
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Darknet: Open Source Neural Networks in C Joseph Redmon 2017
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Announcing GPUs for Google Cloud Platform John Barrus 2016
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Siraj Raval Youtube Channel Siraj Raval 2017
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Amazon Lex Amazon 2017
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Facebook open-sources Caffe2, a new deep learning framework Jordan Novet 2017
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Summaries and notes on Deep Learning research papers Denny Britz 2015
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Comparing Top Deep Learning Frameworks: Deeplearning4j, Torch, Theano, TensorFlow, Caffe, Paddle, MxNet, Keras & CNTK Skymind 2017
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Deep Learning Weekly Jan Bussieck, Malte Baumann 2017
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Microsoft releases CNTK, its open source deep learning toolkit, on GitHub Allison Linn 2016
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The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch Ritchie Ng 2017
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Top Deep Learning Projects Aymeric Damien 2017
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Open-sourcing DeepMind Lab Charlie Beattie, Joel Leibo, Stig Petersen, Shane Legg 2016
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really-awesome-gan Holger Caesar 2017
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What do 50 million drawings look like? Google Research 2017
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Deep Learning Courses Jason Brownlee 2016
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Generative Models Andrej Karpathy, Pieter Abbeel, Greg Brockman, Peter Chen, Vicki Cheung, Rocky Duan, Ian Goodfellow, Durk Kingma, Jonathan Ho, Rein Houthooft, Tim Salimans, John Schulman, Ilya Sutskever, Wojciech Zar 2016
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Music Language Modeling with Recurrent Neural Networks Yoav Zimmerman 2016
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The long game towards understanding dialog Alexandre Lebrun, Antoine Bordes, Leon Bottou, Marco Baroni 2017
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TensorFlow: A proposal of good practices for files, folders and models architecture Author Unknown 2016
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Linear Classification Loss Visualization Andrej Karpathy 2016
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Minimal Neural Network Example Andrej Karpathy 2016
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Tensorflow Tutorials using Jupyter Notebook Sungjoon, bluedisk 2017
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TensorFlow World Amirsina Torfi 2017
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Practical Deep Learning for Coders (fast.ai courses) Rachel Thomas 2017
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Neural Networks demo in Javascript Andrej Karpathy 2016
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The future of deep learning Francois Chollet 2017
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Learning to Learn 2017
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Sentiment Analysis Demo Stanford NLP Stanford NLP 2013
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The Text-Generating RNN Demo Ilya Sutskever 2013
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Toronto Deep Learning Demos Geoffrey Hinton, Ruslan Salakhutdinov, Roger Grosse, Charlie Tang, Nitish Srivastava 2012
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Beginner-level tutorials for TensorFlow Aneeque Ahmed 2017
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Embedding Projector - TensorFlow TensorFlow Team 2017
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PyDial: The Cambridge University Python Multi-domain Statistical Dialogue System Toolkit Stefan Ultes, Lina M. Rojas Barahona, Pei-Hao Su, David Vandyke, Dongho Kim, Inigo Casanueva, Pawel Budzianowski, Nikola Mrkvsic, Tsung-Hsien Wen, Milica Gasic, Steve Young 2017
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An Introduction to MXNet/Gluon Mu Li 2017
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An Introduction to MXNet/Gluon Mu Li 2017
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Lecture Collection | Convolutional Neural Networks for Visual Recognition (Spring 2017) Fei-Fei Li, Justin Johnson, Serena Yeung 2017
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Lasagne Documentation Jan Schlüter 2014
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We today release “Neural Network Console.” Yoshiyuki Kobayashi 2017
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Deep Learning - The Straight Dope Zachary C. Lipton, Mu Li, Alex Smola, Sheng Zha, Aston Zhang, Joshua Z. Zhang, Eric Junyuan Xie 2017
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Deep Meaning Beyond Thought Vectors David McAllester 2017
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Deep Learning Isn't a Dangerous Magic Genie. It's Just Math Oren Etzioni 2017
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Why Deep Learning is Suddenly Changing Your Life Roger Parloff 2016
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Inverse Text Normalization as a Labeling Problem Siri Team 2017
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Written Memories: Understanding, Deriving and Extending the LSTM R2RT 2016
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Deconstruction with Discrete Embeddings R2RT 2017
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Pytorch Tutorial for Fine Tuning/Transfer Learning a Resnet for Image Classification Pytorch 2017
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Getting Started with Deep Learning Matthew Rubashkin 2017
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Question answering on the Facebook bAbi dataset using recurrent neural networks and 175 lines of Python + Keras Stephen Merity 2015
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Deep Learning From Scratch: Theory and Implementation Author Unknown 2017
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Deep Learning with TensorFlow in Python: Convolution Neural Nets Sandipan Dey 2017
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Generative Adversarial Networks (GANs): Engine and Applications Anton Karazeev 2017
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Getting Ready for AI based gaming agents - Overview of Open Source Reinforcement Learning Patterns Faizan Shaikh 2016
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2017 Beginner's Review of GAN Architectures Roman Trusov 2017
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Non-distributional Manaal Faruqui 2015
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Four deep learning trends from ACL 2017: Part 1 Abigail See 2017
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Four deep learning trends from ACL 2017: Part 2 Abigail See 2017
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IPA transcription practice Gretchen McCulloch 2017
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An Interactive History of Chatbots Will Gannon 2017
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Neural Networks Part 1: A Simple Proof of the Universal Approximation Theorem Joe Klein 2017
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Creating your own neural network using TensorFlow Hannah Yan Han 2017
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Tel Aviv Deep Learning Bootcamp Shlomo Kashani 2017
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Sequence to Sequence Deep Learning Quoc Le 2016
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Making Predictions with Sequences Jason Browniee 2017
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What is wrong with convolutional neural nets? Fields Institute, 2017 | Geoffrey Hinton, U of Toronto Geoffrey Hinton 2017
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Microsoft is teaching systems to read, answer and even ask questions Allison Linn 2017
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When (not) to use Deep Learning for NLP Delip Rao 2017
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Neural Network Console Sony 2017
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10 Things Everyone Should Know About Machine Learning Daniel Tunkelang 2017
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Experience Google’s machine learning on your own images, voice and text Kaz Sato 2017
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A Friendly Introduction to Convolutional Neural Networks Ifu Aniemeka 2017
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An Intuitive Guide to Deep Network Architectures Joyce Xu 2017
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Machine Learning for Humans, Part 4: Neural Networks & Deep Learning Vishal Maini 2017
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Machine Learning for Humans, Part 5: Reinforcement Learning Vishal Maini 2017
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The Best Machine Learning Resources Vishal Maini 2017
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