The primary resources for this course are the lecture slides and homework assignments on the front page.

Previous Offerings

A full version of this course was offered in Fall 2019, Fall 2018, Fall 2017 and Spring 2017. Lecture videos from Fall 2019 are available at here; those from Fall 2018 are available here; those from Fall 2017, here; those from Spring 2017, here. An abbreviated version of this course was offered in Fall 2015.

Courses

• Geoff Hinton on Coursera
• Andrew Ng on Coursera
• David Silver's course on reinforcement learning
• Nando de Freitas' course on machine learning
• Andrej Karpathy's course on neural networks

Relevant Textbooks

• Deep Learning
• Sutton & Barto, Reinforcement Learning: An Introduction
• Szepesvari, Algorithms for Reinforcement Learning
• Bertsekas, Dynamic Programming and Optimal Control, Vols I and II
• Puterman, Markov Decision Processes: Discrete Stochastic Dynamic Programming
• Powell, Approximate Dynamic Programming

Misc Links

• Data visualization handout