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Topic Videos (on Canvas/Panopto) Course Materials Introduction to Reinforcement Learning (2022 Live) (2021 Recording) Part 1: Course Overview Part 2: Course Logistics Part 3: Intro to Sequential Decision Making Tabular MDP planning (2022 Live) (2021 Recording) Lecture 2, Part 1: Policy Evaluation Lecture 2, Part 2: Policy Iteration Lecture 2,

Natural language processing (NLP) is a crucial part of artificial intelligence (AI), modeling how people share information. In recent years, deep learning approaches have obtained very high performance on many NLP tasks. In this course, students gain a thorough introduction to cutting-edge neural networks for NLP.

For more information about Stanford's Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai

Course Description This course provides a broad introduction to machine learning and statistical pattern recognition. Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (clustering, dimensionality reduction, kernel methods); learning theory (bias/variance tradeoffs, practical advice); reinforcement learning and adaptive control.

Led by Andrew Ng, this course provides a broad introduction to machine learning and statistical pattern recognition. Topics include: supervised learning (gen...