Machine Learning in Python: Main developments and technology trends in data science, machine learning, and artificial intelligence
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Dive into Deep Learning for NLP
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A Survey of Cross-lingual Word Embedding Models
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Lecture 11: Support Vector Machines III
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Practical Submodularity
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Matthew Staib |
2019 |
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Course notes on Optimization for Machine Learning
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Gabriel Peyre |
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Hidden Markov Models
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Daniel Jurafsky |
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Anna Rogers |
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Psychophysics
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Kohitij Kar |
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End-To-End Speech Recognition with Recurrent Neural Network
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Jose Fonollosa |
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Probability Theory Review for Machine Learning
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Samuel Ieong |
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Thermodynamic limits for neural networks
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Andrew Montanari |
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Deep Learning: A Crash Course Part 2
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Andrew Glassner |
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Daniel Lassiter |
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Dive into Deep Learning
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Aston Zhang |
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Lecture 01: Course Overview
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Neural Machine Translation and Sequence-to-sequence Models: A Tutorial
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Graham Neubig |
2019 |
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Lecture 14: Cost Functions and Regularization
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Theory and Systems for Weak Supervision
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Failures of Gradient Based Deep Learning
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Introduction to Deep Learning
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Razvan Pascanu |
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Arithmetic Coding
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Mathias Winther Madsen |
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Natural Language Ontology
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Friederike Moltmann |
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MLCC 2018 Deep Learning
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Deep Learning Crash Course Part 2
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Ensemble methods: bagging and random forests
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Attributed Network Embedding
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L1 L2 regularization
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David S. Rosenberg |
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N-grams
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Fundamental Concentration Inequalities
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The back-propagation algorithm
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Ryan |
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Deep Learning for Speech and Language: Training a Multilayer Perceptron
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Xiavier Giro-i-Nieto |
2019 |
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Robert Collins |
2007 |
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Graph Neural Networks
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Jure Leskovec |
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Logic and Probability Overview / Probability as Logic
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Reinforcement Learning
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Olivier Pietquin |
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Speech Synthesis: WaveNet
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Antonio Bonafonte |
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The Logic of All p are q
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Larry Moss |
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Learning Structured Predictors
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A Natural Proof System for Natural Language Day 3 Handout
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Lasha Abzianidze and Reinhard Muskens |
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Introduction to Networks
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Transfer Learning for Natural Language Generation - The Case of Open-Domain Dialog
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Bagging Random Forests
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David S. Rosenberg |
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Topics in Computational Linguistics: Week 5: ngrams and language model
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Shu-Kai Hsieh |
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Tutorial: Linking, Extending, Exploiting and Enhancing Tabular Data with Wikidata
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Large-Scale Machine Learning
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NONE |
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Robert Collins |
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Matrix Concentration and Computational Linear Algebra
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Tropp |
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Recent Trends in Deep Learning Based Natural Language Processing
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Reinforcement Learning in Robotics
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Logical Dynamics of Social Interaction Day 4
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Nonparametric Analysis: Nearest Neighbors and Friends
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Samory Kopotufe |
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Martin Krzywinski & Naomi Altman |
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Marian Dörk |
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Convolutional Neural Networks
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Milan Straka |
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Chris Dyer |
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Speech Recognition: Phonetic Context Dependency
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NONE |
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Martin Krzywinski & Naomi Altman |
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Tutorial 5: Text processing
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Marian Dörk |
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Word2Vec, Seq2seq, NMT
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Milan Straka |
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Deep Learning with Python
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François Chollet |
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Muhao Chen, Kai-Wei Chang, Dan Roth |
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Attention Mechanism and Transformer
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Object Detection in 20 Years: A Survey
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Zhengxia Zou |
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Lecture 08: Decision Trees II
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Advanced Hamiltonian Monte Carlo
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Michael Betancourt |
2019 |
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Differential Deep Learning on Graphs and its Applications
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Deep Learning Basics
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NONE |
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Introduction to Optimization
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NONE |
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Formal Semantics of Natural Language Class 4
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Yoad Winter |
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Bayesian Deep Learning
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Yarin Gal |
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Multiple linear regression
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Martin Krzywinski & Naomi Altman |
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Introduction to Machine Learning with SciKit-Learn
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Andreas Muller |
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Mathematics for Machine Learning
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Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong |
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Deep Learning
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Gilles Louppe |
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Understanding the News that Moves Markets
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Gideon Mann |
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Deep Learning A Practitioner's Approach
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Michael M. Bronstein, Joan Bruna, Yann LeCun, Arthur Szlam and Pierre Vandergheynst |
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Policy Gradients
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Pieter Abbeel |
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The Backpropagation Algorithm
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NONE |
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Few-shot Learning: A Survey
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Yaqing Wang |
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Common Evaluation Measures
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Lecture 03: Linear Operators and Convolution
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Robert Collins |
2007 |
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Interpretability: what now?
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Been Kim |
2019 |
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Tips from an ex-PhD student
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Dima Damen |
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Kemal Oflazer |
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Vector Space Models of Meaning Lecture 1
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Martha Lewis and Mehrnoosh Sadrzadeh |
2019 |
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ML Intro 1: Shallow Stuff
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F. Noe |
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Optimal experiment design
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Byran Smucker, Martin Krzywinski & Naomi Altman |
2018 |
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Deep Bayesian Natural Language Processing
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Jen-Tzung Chien |
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Report |
Subgradient Descent
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David S. Rosenberg |
2017 |
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Automatic Speech Recognition
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Daniel Jurafsky, James H. Martin |
2009 |
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Commonsense resources
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Vered Shwartz |
2020 |
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Variational Inference
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Shakir Mohamed |
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Final words
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Vivek Srikumar |
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Towards a Rigorous Science of Interpretable Machine Learning
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Finale Doshi-Velez |
2019 |
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Lecture 05: Edge Detection
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Robert Collins |
2007 |
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Fast Start Differential Calculus
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Daniel Ashlock |
2019 |
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Philosophy of Language
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Zoltán Gendler Szabó |
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Introduction to Gaussian Processes
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Neil D. Lawrence |
2019 |
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Natural Logic Homework 1 Answers
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Larry Moss |
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Yuan Zhou |
2019 |
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Lasha Abzianidze and Reinhard Muskens |
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ACL 2018 Tutorial: Connecting Language and Vision to Actions
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Peter Anderson |
2019 |
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Dive into Deep Learning
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Aston Zhang, Zachary C. Lipton, Mu Li, and Alexander J. Smola |
2019 |
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Report |
Tutorial 4: Temporal analysis
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Marian Dörk |
2020 |
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Report |
EM algorithm
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David S. Rosenberg |
2017 |
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Machine Translation
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Daniel Jurafsky, James H. Martin |
2009 |
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Graph Deep Learning: Methods and Applications
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Muhan Zhang |
2019 |
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Report |
Kernels Part II
|
Lorenzo Rosaco |
2019 |
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Entity Linking to Knowledge Graphs
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Avijit Thawani, Minda Hu, Erdong Hu |
2019 |
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Dimensionality Reduction
|
Victor Kitov |
2019 |
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Report |
Problem Set 02
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2016 |
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CV
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Xuedong Shang |
2019 |
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A Survey of Deep Learning for Scientific Discovery
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Maithra Raghu, Eric Schmidt |
2020 |
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Markov Decision Processes
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Bruno Scherrer |
2019 |
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Completeness Theorems for Syllogistic Fragments
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Larry Moss |
2006 |
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Report |
Deep Learning Tutorial
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Eugenio Piasini |
2019 |
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Report |
Speaker ID II
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Javier Hernando |
2017 |
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Report |
Computational Models of Events Lecture 3 Part b
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James Pustejovsky |
2018 |
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Report |
Embeddings in Natural Language Processing
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Mohammed Taher Pilehvar, Jose Camacho-Collados |
2020 |
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Question Answering
|
Daniel Jurafsky |
2019 |
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Report |
Part II: Explicit Representation for Short Text Understanding
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Zhongyuan Wang, Haixun Wang |
2017 |
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Report |
Introduction to NLP
|
Anna Rogers |
2019 |
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Report |
Decoding the neural algorithms that underlie behavior
|
Ethan Meyers |
2019 |
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Machine Learning is Fun! The world?s easiest introduction to Machine Learning - Part 6
|
Adam Geitgey |
2016 |
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Report |
Computational Models of Events Lecture 5 Part c
|
James Pustejovsky |
2018 |
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Report |
Interpretability the who what why and how
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Sanmi Koyejo |
2019 |
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Replication
|
Paul Blainey, Martin Krzywinski & Naomi Altman |
2014 |
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Entropy, Relative Entropy, and Mutual Information
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Cover and Thomas |
2019 |
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Tutorial 7: Network analysis
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Marian Dörk |
2020 |
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Report |
The Open Handbook of Formal Epistemology
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Richard Pettigrew, Jonathan Weisberg |
2019 |
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Emergent linguistic structure in deep contextual neural word representations
|
Christopher Manning |
2019 |
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Report |
Representing and comparing probabilities with kernels: Part 3
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Arthur Gretton |
2018 |
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Report |
Machine Learning Engineering (Chapter 2)
|
Andriy Burkov |
2019 |
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Emotions in language: Linguistic and computational approaches
|
Diana Santos, Belinda Maia |
2016 |
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Report |
Sentence Representation Learning: Evaluation and the State of the Art
|
Ellie Pavlick |
2018 |
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Report |
CS 221 Foundations
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NONE |
2019 |
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Lecture 17: Convolutional Neural Networks
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2016 |
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Kernels Part I
|
Lorenzo Rosaco |
2019 |
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Report |
CS 520: What is a Knowledge Graph?
|
Mikhail Galkin |
2020 |
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Backpropagation for a Linear Layer
|
Justin Johnson |
2019 |
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Communities
|
Luna Dong, Christos Faloutsos, Audrey Kan, Jun Ma, Subho Mukherjee |
2018 |
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Report |
RL/Planning + Humans
|
Anca Dragan |
2019 |
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Report |
Word representations
|
Erhard Hinrichs and Daniël de Kok |
2018 |
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Report |
Machine Learning and the Physical Sciences
|
Giuseppe Carleo |
2019 |
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Report |
Classification evaluation
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Martin Krzywinski & Naomi Altman |
2016 |
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Report |
The Matrix Calculus You Need for Deep Learning
|
Terence Parr |
2019 |
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Making Better Use of the Crowd: How Crowdsourcing Can Advance Machine Learning Research
|
Jennifer Wortman Vaughan |
2018 |
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Report |
Machine Learning Engineering (Preface)
|
Andriy Burkov |
2019 |
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Report |
On Linear Regression: Regularization, Probabilistic Interpretation, and Gradient Descent
|
Karl Stratos |
2018 |
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Report |
Hands-on Machine Learning with Scikit-Learn, Keras & Tensorflow
|
Auerlien Geron |
2019 |
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Semantics for Semantic Parsing
|
Mark Steedman, Mike Lewis, Siva Reddy, Mirella Lapata |
2014 |
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Report |
Probabilistic Programming
|
Frank Wood |
2015 |
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Advanced topics in end-to-end speech recognition Hybrid CTC/ Attention Architecture for End-to-End Speech Recognition
|
Takaaki Hori, Shinji Watanabe, Jonathan Le Roux, John Hershey |
2019 |
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Report |
IAML: Dimensionality Reduction
|
Victor Lavrenko |
2019 |
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Knowledge Graphs for Natural Language Processing
|
Jose Manuel Gomez-Perez |
2019 |
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Report |
How to Wreck a Nice Beach
|
Eric Fosler-lussier |
2019 |
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Report |
Lecture 17: Stabilization and Mosaicing
|
Robert Collins |
2007 |
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Report |
Knowledge Extraction and Inference from Text: Shallow, Deep, and Everything in Between Part 1
|
Partha Talukdar |
2019 |
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Report |
Graph Formalisms for Meaning Representations Day 2
|
Sorcha Gilroy and Adam Lopez |
2018 |
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Deep Learning for Biomedicine
|
Truyen Tran |
2019 |
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What about Morphology?
|
Erhard Hinrichs and Daniël de Kok |
2018 |
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Dynamical Systems
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NONE |
2019 |
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Markov models - training and evaluation of hidden Markov models
|
Jasleen K. Grewal, Martin Krzywinski and Naomi Altman |
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Discourse Analysis and Its Applications
|
Shafq Joty |
2019 |
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Report |
A Modern Introduction to Online Learning
|
Francesco Orabona |
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MLE
|
David S. Rosenberg |
2017 |
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Statistical Parsing
|
Daniel Jurafsky, James H. Martin |
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Text as data: An overview
|
Kenneth Benoit |
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Submodularity
|
Stefanie Jegelka |
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Basic Concepts from Information Theory
|
Roni Rosenfeld |
1997 |
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Report |
A Survey on Deep Learning Based Brain Computer Interface: Recent Advances and New Frontiers
|
Xiang Zhang |
2019 |
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Report |
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|
Robert Collins |
2007 |
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Report |
Deep Chit-Chat: Deep Learning for Chatbots
|
Wei Wu |
2019 |
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Report |
Language modeling with Tree-Adjoining Grammars Day 2 Linguistic analyses with LTAG
|
Kata Balogh and Simon Petitjean |
2018 |
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Report |
Bandit Problems Part 1 Stochastic Bandits
|
Emilie Kaufmann |
2019 |
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Report |
Probability and Counterfactuals Lecture 2
|
Fabrizio Cariani and Paolo Santorio |
2019 |
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Report |
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|
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2019 |
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