Topic 8: Artificial Intelligence 493


Title (link) Author Date Votes Error Reviews
A Bayesian Approach to Biomedical Text Summarization Milad Moradi, Nasser Ghadiri 2016
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Reinforcement Learning Florentin Woergoetter, Bernd Porr 2008
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Policy Gradient Methods Jan Peters 2010
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Title (link) Author Date Votes Error Reviews
How IBM Watson is Taking on The World Khushbu Shah 2016
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[Infographic] 10 Popular TV Shows on Data Science and Artificial Intelligence Kunal Jain 2016
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Stanford AI Director: How AI & Computer Vision will Drive our Future Fei-Fei Li 2017
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Reinforcement Learning and DQN, learning to play from pixels Ruben Fiszel 2015
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Artificial Intelligence, Revealed by Facebook Pranavathiyani G 2017
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Deep Learning #1: Setting up AWS & Image Recognition Rutger Ruizendaal 2017
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Learning AI If You Suck at Math?—?P6?—?Math Notation Made Easy! Daniel Jeffries 2017
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Learning AI if You Suck at Math?—?P5?—?Deep Learning and Convolutional Neural Nets in Plain English! Daniel Jeffries 2017
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Learning AI if You Suck at Math?—?P4?—?Tensors Illustrated (with Cats!) Daniel Jeffries 2017
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Learning AI if You Suck at Math?—?P3?—?Building an AI Dream Machine or Budget Friendly Special Daniel Jeffries 2017
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Learning AI if You Suck at Math?—?Part Two?—?Practical Projects Daniel Jeffries 2017
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Learning AI if You Suck at Math Daniel Jeffries 2017
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Artificial Intelligence: past, present, future Eugenio Culurciello 2017
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Rohan #2: Artificial intelligence, ?Progress/?Time Rohan Kapur 2016
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Rohan #7: Can artificial intelligence possess human-like minds? Rohan Kapur 2016
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Learning to Segment Piotr Dollar 2016
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The Rise of Artificial Intelligence through Deep Learning Yoshua Bengio 2017
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An Overview of Multi-Task Learning in Deep Neural Networks Sebastian Ruder 2017
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Deep Learning and the Future of Artificial Intelligence(AI) | Facebook AI Director Yann LeCun Yann LeCun 2017
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Technology at work: The future of employment Michael A Osborne 2016
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Tutorial: Deep Reinforcement Learning David Silver 2016
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Recognizing and Learning ?Object Categories: Year 2009 Li Fei-Fei, Rob Fergus, Antonio Torralba 2009
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Deep Learning & Feature Learning Methods for Vision Rob Fergus, Kai Yu, Marc’Aurelio Ranzato, Honglak Lee, Ruslan Salakhutdinov, Graham Taylor 2012
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ConvNetJS Deep Q Learning Demo Andrej Karpathy 2013
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ConvnetJS demo: Image "Painting" Andrej Karpathy 2013
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Deep Reinforcement Learning: Pong from Pixels Andrej Karpathy 2016
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Introduction to Q-Learning Aneek Das 2017
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Simple Reinforcement Learning with Tensorflow Part 0: Q-Learning with Tables and Neural Networks Arthur Juliani 2016
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Simple Reinforcement Learning in Tensorflow: Part 1 - Two-armed Bandit Arthur Juliani 2016
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Simple Reinforcement Learning with Tensorflow Part 1.5: Contextual Bandits Arthur Juliani 2016
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Simple Reinforcement Learning with Tensorflow: Part 2 - Policy-based Agents Arthur Juliani 2016
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Simple Reinforcement Learning with Tensorflow: Part 3 - Model-Based RL Arthur Juliani 2016
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Simple Reinforcement Learning with Tensorflow Part 4: Deep Q-Networks and Beyond Arthur Juliani 2016
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Simple Reinforcement Learning with Tensorflow Part 5: Visualizing an Agent’s Thoughts and Actions Arthur Juliani 2016
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Simple Reinforcement Learning with Tensorflow Part 6: Partial Observability and Deep Recurrent Q-Networks Arthur Juliani 2016
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Simple Reinforcement Learning with Tensorflow Part 7: Action-Selection Strategies for Exploration Arthur Juliani 2016
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Simple Reinforcement Learning with Tensorflow Part 8: Asynchronous Actor-Critic Agents (A3C) Arthur Juliani 2016
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Introduction to reinforcement learning and OpenAI Gym Justin Francis 2017
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Image Recognition - TensorFlow Tutorials TensorFlow Team 2017
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Learning to Communicate Pieter Abbeel, Igor Mordatch, Ryan Lowe, Jon Gauthier & Jack Clark 2017
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Demystifying Deep Reinforcement Learning Tambet Matiisen 2015
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Deep Reinforcement Learning with Neon Tambet Matiisen 2015
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Let’s evolve a neural network with a genetic algorithm—code included Matt Harvey 2017
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Evolve a neural network with a genetic algorithm Matt Harvey 2017
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Bayesian Generative Modeling Jason Eisner 2011
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Constructing and Mining Web-scale Knowledge Graphs Evgeniy Gabrilovich, Nicolas Usunier 2013
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Towards Artificial General Intelligence: Oriol Vinyals Oriol Vinyals 2017
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Reinforcement Learning w/ Keras + OpenAI: Actor-Critic Models Yash Patel 2017
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Yoshua Bengio on intelligent machines Yoshua Bengio 2017
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Jeff Dean’s Lecture for YC AI Jeff Dean 2017
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Reinforcement Learning – Policy Optimization Pieter Abbeel, John Schulman 2017
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Why is Go hard for computers to play? DeepMind 2016
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Tutorial: Deep Reinforcement Learning David Silver 2016
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Visual Dialog: Towards AI agents that can see, talk, and act Dhruv Batra 2017
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Deep reinforcement learning Hado van Hasselt 2017
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Deep Reinforcement Learning, Decision Making, and Control Sergey Levine, Chelsea Finn 2017
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Recent Image Search Techniques: Introduction Sung-Eui Yoon 2016
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VQA -> Visual Dialog Devi Parikh 2017
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Reinforcement Learning: Basic concepts Joelle Pineau 2017
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RL in the industry Nicolas Le Roux 2017
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Steps Towards Continual Learning Satinder Singh 2017
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Real World Interactive Learning Alekh Agarwal, John Langford 2017
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Temporal-Difference Learning Rich Sutton 2017
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Theory of Reinforcement Learning Csaba Szepesvari 2017
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Safe Reinforcement Learning Philip S. Thomas 2017
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Domain Randomization for Cuboid Pose Estimation Jonathan Tremblay 2017
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Representations in Deep Reinforcement Learning Pieter Abbel 2017
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5 Ways to Get Started with Reinforcement Learning Harshvardhan Gupta 2017
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Solving the Schrodinger equation with Deep Learning Steven Steinke 2017
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Day 22: How to build an AI Game Bot using OpenAI Gym and Universe Harini Janakiraman 2017
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Understanding your Data with Bayesian Networks (in Python) Bartek Wilczynski 2014
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Keras plays catch, a single file Reinforcement Learning example Eder Santana 2017
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Detecting Lane Lines?—?Udacity SDCND David Clark 2017
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Classifying Traffic Signs David Clark 2017
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End-to-End Self-Driving Car Using Behavioral Cloning David Clark 2017
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Advanced Lane-Detection for Self-Driving Cars David Clark 2017
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AlphaGo Zero: Learning from Scratch Demis Hassabis, David Silver 2017
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Build a Game-playing Agent Ryan Shrott 2017
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Deep Reinforcement Learning Tutorial awjuliani 2017
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Q-Learning Step-By-Step Tutorial John McCullock 2012
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How to Make a Racist AI without Really Trying Rob Speer 2017
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Numerical Computation for Deep Learning - AI with the Best Ian Goodfellow 2017
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Capsule Networks are Shaking up AI - Here's How to Use Them Nick Bourdakos 2017
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Advanced Reinforcement Learning George Konidaris 2017
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Reinforcement Learning: An introduction Vukosi Marivate and Benjamin Rosman 2017
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The 10 Deep Learning Methods AI Practitioners Need to Apply James Le 2017
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Deep Learning for Speech/Language Processing Li Deng 2015
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Deep Q-Networks Volodymyr Mnih 2017
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Derivative-free and Evolutionary Methods Xi Chen 2017
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Model-Based Deep Reinforcement Learning Chelsea Finn 2017
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Deep Reinforcement Learning Bootcamp Lecture 10a: Utilities Pieter Abbeel 2017
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Inverse Reinforcement Learning Chelsea Finn 2017
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Vision Y LeCun 2017
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EECS 442 Computer Vision S. Lazebnik 2017
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Deep Reinforcement Learning John Schulmann 2016
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Human-level control through deep reinforcement learning Bowen Xu 2017
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Temporal-Difference Learning Richard Sutton 2016
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Reinforcement Learning Examples Meg Aycinena And Emma Brunskill 2017
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RL with function approximation Richard Sutton 2015
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Reinforcement Learning Andrew W. Moore 2001
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Searching: Deterministic single-agent Andrew W. Moore 2001
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constraint satisfaction and scheduling Andrew W. Moore 2001
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Algorithms for Playing and Solving games Andrew W. Moore 2001
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Games with Hidden Information Andrew W. Moore 2001
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Iterative Improvement Search Andrew W. Moore 2001
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Robot Motion Planning Andrew W. Moore 2001
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Non-zero-sum Game Theory, Auctions and Negotiation Andrew W. Moore 2001
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A Brief Survey of Deep Reinforcement Learning Kai Arulkumaran, Marc Peter Deisenroth, Miles Brundage, Anil Anthony Bharath 2017
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AlphaGo Google 2017
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AlphaGo Tutorial Slides Google 2017
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FAIR COCO Object Detection Sergey Zagoruyko, Tsung-Yi Lin 2015
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Deep Reinforcement Learning David Silver 2017
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Tutorial: Deep Reinforcement Learning David Silver 2017
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Knowledge Graphs:from a Fistful of Triples to Deep Data and Deep Text Gerhard Weikum 2015
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What Computers Should Know Gerhard Weikum 2016
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Big Text: from Names and Phrases to Entities and Relations Gerhard Weikum 2014
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Bayesian Generative Modeling Jason Eisner 2011
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Sparse Modeling in Image Processing and Deep Learning Michael Elad 2018
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From People2Vec to EmotionalAI Author Unknown 2018
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Bienvenue dans le monde de l’intelligence artificielle Myriam Côté 2018
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Bibliothèques & Installation party Gaétan Marceau Caron 2018
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Apprentissage profond Gaétan Marceau Caron 2018
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Apprentissage Automatique Alain Tapp 2018
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Application : traitement d’images Margaux Luck 2017
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Zero-Shot Learning for Computer Vision Thomas Mensink, Efstratios Gavves, Zeynep Akata, Cees Snoek 2017
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Nuts and bolts of building AI applications using Deep Learning Andrew Ng 2016
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Interpretable Discovery in Large Image Data Sets Kiri L. Wagstaff and Jake Lee 2017
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Interpretability for AI Safety Victoria Krakovna 2017
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Deep Reinforcement Learning through Policy Optimization Pieter Abbeel, John Schulman 2017
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Reinforcement Learning and Artificial Neural Networks Pierre de Lacaze 2016
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Submodularity in Speech/NLP Jeffrey A. Bilmes 2014
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Learning to Do Author Unknown 2017
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Deep Learning for Computer Vision Lex Fridman 2017
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Commonsense for Machine Intelligence: Text to Knowledge and Knowledge to Text Gerard de Melo, Niket Tandon and Aparna S. Varde 2017
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Deep Learning for Speech Generation and Synthesis Yao Qian, Frank K. Soong 2014
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Beyond EM: Bayesian Techniques for HLT Hal Daume III 2006
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Deep Learning for Conversational AI Pei-Hao Su, Nikola MrköiÊ, Iñigo Casanueva, Ivan VuliÊ 2018
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Learning to Do Author Unknown 2017
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Multi-view representation learning for speech (and language) Karen Livescu 2018
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Deep Learning for Conversational AI Tsung­Hsien Wen, Ivan Vuli?, Nikola Mrkši? and Pei­Hao Su 2018
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Deep Learning for Conversational AI Pei-Hao Su, Nikola MrköiÊ, Iñigo Casanueva, Ivan VuliÊ 2018
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Deep Learning for Computer Vision Lex Fridman 2017
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Embodied Agents & Environments Abhishek Das 2018
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Embodied Agents & Environments (Part 2) Abhishek Das 2018
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Reinforcement Learning in Language and Vision Abhishek Das 2018
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Transfer Learning Author Unknown 2018
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Variational Bayes and beyond: Bayesian inference for big data Tamara Broderick 2018
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Part II: Automated, Scalable Bayesian Inference via Data Summarization' 'http://www.tamarabroderick.com/tutorial_2018_icm Tamara Broderick 2018
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Title (link) Lecturer Date Votes Error Reviews
Deep Learning and the Future of AI Yann LeCun 2016
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Facebook AI Director: The Next Frontier in AI, Unsupervised Learning Yann LeCun 2017
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Games II Percy Liang 2017
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Bayesian networks III Percy Liang 2017
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Learning Sklearn Percy Liang 2017
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CSPs II Percy Liang 2017
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AlphaGo Percy Liang 2017
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Bayesian networks I Percy Liang 2017
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Constraint Satisfaction Problems (CSPs) Percy Liang 2017
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Games I Percy Liang 2017
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Deep Reinforcement Learning Percy Liang 2017
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MDPs I Percy Liang 2017
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Search II Percy Liang 2017
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CSPs I Percy Liang 2017
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Bayesian networks II Percy Liang 2017
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Search DP, UCS, A* Percy Liang 2017
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Search I Percy Liang 2017
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Adversarial Search Ansaf Salleb-Aouissi 2014
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Problem Solving:Search Ansaf Salleb-Aouissi 2014
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Intelligent Agent (continued) Ansaf Salleb-Aouissi 2014
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A* optimality Local Search Ansaf Salleb-Aouissi 2014
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Logical Agents Ansaf Salleb-Aouissi 2014
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Uncertainty George Konidaris 2016
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Introduction to Artificial Intelligence George Konidaris 2016
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Informed Search George Konidaris 2016
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GameTheory George Konidaris 2016
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Search George Konidaris 2016
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Bayesian Networks II George Konidaris 2016
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Robot Motion Planning George Konidaris 2016
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Adversarial Search George Konidaris 2016
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Computing Game-Theoretic Solutions for Security George Konidaris 2016
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Probabilistic Planning George Konidaris 2016
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Bayesian Networks George Konidaris 2016
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A*: Proof of Optimality George Konidaris 2016
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Reinforcement Learning George Konidaris 2016
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Markov Decision Processes Dan Klein and Pieter Abbeel 2014
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Advanced Applications: Computer Vision and Robotics * Dan Klein and Pieter Abbeel 2014
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Search Dan Klein and Pieter Abbeel 2014
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Bayes Nets: Inference Dan Klein and Pieter Abbeel 2014
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Uncertainty and Utilities Dan Klein and Pieter Abbeel 2014
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Bayes Nets: Independence Dan Klein and Pieter Abbeel 2014
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Introduction Dan Klein and Pieter Abbeel 2014
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Adversarial Search Dan Klein and Pieter Abbeel 2014
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CSPs Dan Klein and Pieter Abbeel 2014
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Reinforcement Learning I Dan Klein and Pieter Abbeel 2014
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Reinforcement Learning II Dan Klein and Pieter Abbeel 2014
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Markov Decision Processes II Dan Klein and Pieter Abbeel 2014
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Bayes Nets: Sampling Dan Klein and Pieter Abbeel 2014
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Uncertainty Chuck Dyer 2018
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Introduction Chuck Dyer 2018
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Game Playing Chuck Dyer 2018
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Bayesian Networks Chuck Dyer 2018
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Face Detection and Recognition I Chuck Dyer 2018
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Introduction Chuck Dyer 2018
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Informed Search Chuck Dyer 2018
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Face Detection and Recognition II Chuck Dyer 2018
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Constraint Satisfaction Problems Chuck Dyer 2018
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Genetic Algorithms Chuck Dyer 2018
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Uninformed Search Chuck Dyer 2018
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Deep Graphical Models III David McAllester 2017
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AlphaZero David McAllester 2017
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In Search of AGI David McAllester 2017
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Regularization David McAllester 2017
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Computer vision - pooling and subsampling Hugo Larochelle 2017
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Computer vision - example Hugo Larochelle 2017
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Computer vision Hugo Larochelle 2017
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Computer vision - data set expansion Hugo Larochelle 2017
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Computer vision - motivation Hugo Larochelle 2017
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Computer vision - convolutional RBM Hugo Larochelle 2017
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Computer vision - parameter sharing Hugo Larochelle 2017
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Computer vision - object recognition Hugo Larochelle 2017
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Computer vision - local connectivity Hugo Larochelle 2017
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Learning+Reasoning Alexander Amini 2018
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Bayesian Decision Theory Ethem Alpaydın 2014
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Reinforcement Learning Ethem Alpaydın 2014
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Introduction to Bayesian methods continued 2 David Sontag 2016
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Learning theory and Decision trees David Sontag 2016
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Introduction to Bayesian methods David Sontag 2016
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Introduction to Bayesian methods continued 1 David Sontag 2016
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Introduction to Learning David Sontag 2016
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Learning theory David Sontag 2016
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Bayesian networks David Sontag 2016
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A History of AI David Sontag 2016
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Adversarial Learning Roger Grosse 2018
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Learning Theory Matt Gormley 2016
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Perceptron and Kernels Matt Gormley 2016
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Bayesian Networks Matt Gormley 2016
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MLE/MAP and Naïve Bayes Matt Gormley 2016
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Regularization and Perceptron Matt Gormley 2016
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Reinforcement Learning Maria-Florina Balcan 2015
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Bayesian Network Tom M. Mitchell 2015
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Boosting Approach to ML Perceptron, Margins, Kernels Maria-Florina Balcan 2015
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Graphical models and Bayes Nets Tom M. Mitchell 2015
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Graphical models and Bayes Nets Tom M. Mitchell 2015
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Naive Bayes Tom M. Mitchell 2015
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Bayes Classifiers Tom M. Mitchell 2015
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Graphical models and Bayes Nets Tom M. Mitchell 2015
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Graphical models and Bayes Nets Tom M. Mitchell 2015
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Naive Bayes Tom M. Mitchell 2015
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Graphical models and Bayes Nets Tom M. Mitchell 2015
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Experiences with MapReduce, an Abstraction for Large-Scale Computation Christopher Manning 2017
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Learning to Search Kai-Wei Chang 2017
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Turing machines Shay Cohen 2017
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Turing machines and linear bounded automata Shay Cohen 2017
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Linear Models Continued: Perceptron & Logistic Regression Marine Carpuat 2017
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Regular Languages Lecture #2 Andrew McCallum 2007
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Logical Forms Sameer Singh 2017
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Logical Forms Sameer Singh 2017
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Lecture 12: Bayesian Inference, Unsupervised NLP Kevin Gimpel 2017
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Lecture 14: Finish up Bayesian/Unsupervised NLP, Start Structured Prediction Kevin Gimpel 2017
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Lecture 13: Introduction to Bayesian Nonparametrics for NLP Kevin Gimpel 2017
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Lecture 10: Introduction to Bayesian NLP Kevin Gimpel 2017
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CS11-747 Neural Networks for NLP Reinforcement Learning for NLP Graham Neubig 2017
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CS11-747 Neural Networks for NLP Advanced Search Algorithms Graham Neubig 2017
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CS11-747 Neural Networks for NLP Adversarial Methods Zihang Dai & Qizhe Xie Graham Neubig 2017
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Title (link) Lecturer Date Votes Error Reviews
How do Artificial Neural Networks learn? rubikscode 2018
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Backpropagation Algorithm in Artificial Neural Networks rubikscode 2018
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ARTIFICIAL INTELLIGENCE 2E David Poole, Alan Mackworth 2017
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Allen Institute for Artificial Intelligence: datasets Allen Institute 2017
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The Behance Artistic Media Dataset Michael Wilber, Chen Fang, Hailin Jin, Aaron Hertzmann, John Collomosse, Serge Belongie 2017
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twentybn datasets Christian Thurau, Roland Memisevic, Florian Hoppe, Ingo Bax 2016
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Kinetics: YouTube Video Understanding Dataset Will Kay, Joao Carreira, Karen Simonyan, Brian Zhang, Chloe Hillier, Sudheendra Vijayanarasimhan, Fabio Viola, Tim Green, Trevor Back, Paul Natsev, Mustafa Suleyman, Andrew Zisserman 2017
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THOR Challenge Roozbeh Mottaghi, Eric Kolve, Daniel Gordon 2017
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The Spoken Wikipedia Corpora Natural Language Systems Group 2017
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Image Captions 2010 Cyrus Rashtchian, Peter Young, Micah Hodosh, and Julia Hockenmaier 2010
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Image Captions 2013 Cyrus Rashtchian, Peter Young, Micah Hodosh, and Julia Hockenmaier 2013
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Microsoft Speech Language Translation (MSLT) Corpus Author Unknown 2017
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Title (link) Author Date Votes Error Reviews
Sign-Recognition Kashyap Raval 2017
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Mycroft AI Open Source Artificial Intelligence Joshua Montgomery 2017
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OpenAI Baselines Szymon Sidor, Matthias Plappert 2017
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Visdom Facebook 2017
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A Hierarchical Approach for Generating Descriptive Image Paragraphs Jonathan Krause, Justin Johnson, Ranjay Krishna, Fei-Fei Li 2017
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Universe Author Unknown 2017
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tf-agent Andrej Karpathy 2017
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JgibbLDA: A Java Implementation of Latent Dirichlet Allocation (LDA) Xuan-Hieu Phan and Cam-Tu Nguyen 2008
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TorchMoji Bjarke Felbo, Alan Mislove, Anders Søgaard, Iyad Rahwan and Sune Lehmann 2017
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Competitive Multi-Agent Environments OpenAI 2017
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BayesPy Jaakko Luttinen 2017
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BayesPy Introduction Jaakko Luttinen 2017
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BayesPy - Bayesian Python Jaakko Luttinen 2017
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Bayesian Python: Bayesian inference tools for Python Jaakko Luttinen 2017
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libpgm Charles Cabot 2012
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Bayes Net Finder Bartek Wilczynski, Norbert Dojer 2015
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Gym - 32 levels of original Super Mario Bros Philip Paquette 2017
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PyTorch implementation of Advantage Actor Critic (A2C), PPO, ACKTR Ilya Kostrikov 2017
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Multi-Agent Particle Environment Igor Mordatch, Pieter Abbeel 2017
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Neural Adaptive Machine Translation Marcello Federico 2017
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Pomegranate Author Unknown 2018
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Quick NLP Outcast of Music 2018
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OpenAI Gym Greg Brockman, Vicki Cheung, Ludwig Pettersson, Jonas Schneider, John Schulman, Jie Tang, Wojciech Zaremba 2018
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Transfer Learning for NLP: Sentiment Analysis on Amazon Reviews feedly 2018
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PyDial Dialogue Systems Group 2017
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Reinforcement Learning: An Introduction (2nd ed) Richard S. Sutton and Andrew G. Barto 2017
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Artificial Intelligence and Games Georgios N. Yannakakis and Julian Togelius 2018
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Reinforcement Learning: An Introduction Richard S. Sutton, Andrew G. Barto 2018
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Deep Reinforcement Learning: An Overview Yuxi Li 2017
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Algorithms for Reinforcement Learning Csaba Szepesvari 2009
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Artificial Intelligence’s Next Big Step: Reinforcement Learning Mary Branscombe 2017
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AI, Deep Learning, and Machine Learning: A Primer Frank Chen 2017
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A Beginner's Guide to Reinforcement Learning (for Java) Adam Gibson, Chris Nicholson, Josh Patterson 2017
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Reinforcement Learning Part 1: Q-Learning and Exploration Travis DeWolf 2012
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Recurrent vs Recursive Neural Networs: Which is better for NLP? crscardellino, gung 2015
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Deep Reinforcement Learning Demystified (Episode 0) Moustafa Alzantot 2017
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Episode 1 - Genetic Algorithm for Reinforcement Learning Moustafa Alzantot 2017
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Deep Reinforcement Learning Demystifed (Episode 2) - Policy Iteration, Value Iteration and Q-Learning Moustafa Alzantot 2017
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FigureQA: an annotated figure dataset for visual reasoning Author Unknown 2017
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New Theory Cracks Open the Black Box of Deep Learning Natalie Wolchover 2017
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Under the Hood with Reinforcement Learning - Understanding Basic RL Models William Vorhies 2017
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Artificial Intelligence Demystified Guest Blog 2016
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A Guide to NLP: A Confluence of AI and Linguistics Pramod Chandrayan 2017
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IBM Code Patterns and the Future of AI Tom Smith 2017
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Thinking out loud: hierarchical and interpretable multi-task reinforcement learning Tianmin Shu, Caiming Xiong, James Bradbury 2017
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A domain specific language for automated rnn architecture search Martin Schrimpf, Stephen Merity 2017
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Exploring Recurrent Neural Networks Packtpub 2018
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Understanding Capsule Networks?—?AI’s Alluring New Architecture Nick Bourdakos 2018
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Decision Trees?—?Understanding Explainable AI Grant Holtes 2018
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Neural network AI is simple. So... Stop pretending you are a genius. Brandon Wirtz 2018
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Beat Atari with Deep Reinforcement Learning! (Part 0: Intro to RL) Adrien Lucas Ecoffet 2017
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Beat Atari with Deep Reinforcement Learning! (Part 1: DQN) Adrien Lucas Ecoffet 2017
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Beat Atari with Deep Reinforcement Learning! (Part 2: DQN improvements) Adrien Lucas Ecoffet 2017
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Reinforcement Learning?—?Part 2 Prakhar Mishra 2017
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Reinforcement Learning?—?Part 3 Prakhar Mishra 2017
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Reinforcement Learning?—?Part 4 Prakhar Mishra 2017
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10 Applications of Artificial Neural Networks in Natural Language Processing Olga Davydova 2017
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Expressive Speech Synthesis with Tacotron Yuxuan Wang, RJ Skerry-Ryan 2018
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Artificial Intelligence Complete Courses Patrick Henry Winston 2018
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An introduction to Reinforcement Learning Thomas Simonini 2018
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Introduction to Various Reinforcement Learning Algorithms. Part II (TRPO, PPO) Steeve Huang 2018
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Reinforcement Learning w/ Keras + OpenAI: DQNs Yash Patel 2017
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How to build a Neural Network with Keras Niklas Donges 2018
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Reinforcement Learning w/ Keras + OpenAI: Actor-Critic Models Yash Patel 2017
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A (Long) Peek into Reinforcement Learning Lilian Weng 2018
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ANN Visualizer: A python library for visualizing Artificial Neural Networks (ANN) Kirti Bakshi 2018
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What’s hot in AI: Deep reinforcement learning Sam Charrington 2018
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Multinomial Naive Bayes Classifier for Text Analysis (Python) Syed Sadat Nazrul 2018
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Diving deeper into Reinforcement Learning with Q-Learning Thomas Simonini 2018
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Reinforcement Learning Demystified: A Gentle Introduction Mohammed Ashraf 2018
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Reinforcement Learning Demystified: Markov Decision Processes (Part 1) Mohammed Ashraf 2018
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Reinforcement Learning Demystified: Markov Decision Processes (Part 2) Mohammed Ashraf 2018
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High-Level Explanation of Variational Inference Jason Eisner 2011
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Comprehensive & Practical Inferential Statistics Guide for data science NSS 2017
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Write an AI to win at Pong from scratch with Reinforcement Learning Dhruv Parthasarathy 2016
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TD Learning?—?Richard Sutton Presentation at Reinforcement Learning Summer School, Montreal 2017 Ranko Mosic 2017
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My Journey to Reinforcement Learning?—?Part 0: Introduction Jae Duk Seo 2018
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Introduction to Naive Bayes Classification Devin Soni 2018
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TensorFlow Speech Recognition Challenge— Solution Outline Armin Oliya 2018
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The Ultimate Guide To Speech Recognition With Python David Amos 2018
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Open Source Toolkits for Speech Recognition Cindi Thompson 2017
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Creating an open speech recognition dataset for (almost) any language Andreas Klintberg 2017
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Introductory Guide to Artificial Intelligence Egor Dezhic 2018
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AI-Playbook a16z 2017
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Reinforcement Learning MDPs Ray Zhang 2018
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Introductory Guide to Artificial Intelligence Egor Dezhic 2018
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Reinforcement Learning?—?Part 1 Prakhar Mishra 2017
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Reinforcement Learning?—?Part 2 Prakhar Mishra 2017
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Reinforcement Learning?—?Part 3 Prakhar Mishra 2017
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Reinforcement Learning?—?Part 4 Prakhar Mishra 2017
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Reinforcement Learning?—?Part 5 Prakhar Mishra 2018
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Reinforcement Learning?—?Part 6 Prakhar Mishra 2018
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Must know Information Theory concepts in Deep Learning (AI) Abhishek Parbhakar 2018
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AI Safety via Debate Geoffrey Irving, Dario Amodei 2018
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Explain yourself, machine. Producing simple text descriptions for AI interpretability. Luke Oakden-Rayner 2018
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Must know Information Theory concepts in Deep Learning (AI) A:bhishek Parbhakar 2018
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Graphs & paths: A*, getting out of a maze. David Pynes 2018
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Tag2Image and Image2Tag?—?Joint representations for images and text Amine Aoullay 2018
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An Introductory Example of Bayesian Optimization in Python with Hyperopt William Koehrsen 2018
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Applying transfer learning in NLP and CV Lars Hulstaert 2018
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Grokking Deep Learning Andrew W. Trask 2016
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Beginners Ask “How Many Hidden Layers/Neurons to Use in Artificial Neural Networks?” Ahmed Gad 2018
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NLP's ImageNet moment has arrived Sebastian Ruder 2018
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