Great courses (DVD). Science & mathematics. Engineering

Directed by The Great Courses

Lecturer: Professor Michael L. Littman, Brown University

This series teaches you about machine-learning programs and how to write them in the Python programming language. For those new to Python, a "get-started" tutorial is included. Professor Michael L. Littman covers major concepts and techniques, all illustrated with real-world examples such as medical diagnosis, game-playing, spam filters, and media special effects

Rated TVPG

Mode of access: World Wide Web

Episode 1

Telling the Computer What We Want

Episode 2

Starting with Python Notebooks and Colab

Episode 3

Decision Trees for Logical Rules

Episode 4

Neural Networks for Perceptual Rules

Episode 5

Opening the Black Box of a Neural Network

Episode 6

Bayesian Models for Probability Prediction

Episode 7

Genetic Algorithms for Evolved Rules

Episode 8

Nearest Neighbors for Using Similarity

Episode 9

The Fundamental Pitfall of Overfitting

Episode 10

Pitfalls in Applying Machine Learning

Episode 11

Clustering and Semi-Supervised Learning

Episode 12

Recommendations with Three Types of Learning

Episode 13

Games with Reinforcement Learning

Episode 14

Deep Learning for Computer Vision

Episode 15

Getting a Deep Learner Back on Track

Episode 16

Text Categorization with Words as Vectors

Episode 17

Deep Networks That Output Language

Episode 18

Making Stylistic Images with Deep Networks

Episode 19

Making Photorealistic Images with GANs

Episode 20

Deep Learning for Speech Recognition

Episode 21

Inverse Reinforcement Learning from People

Episode 22

Causal Inference Comes to Machine Learning

Episode 23

The Unexpected Power of Over-Parameterization

Episode 24

Protecting Privacy within Machine Learning

Episode 25

Mastering the Machine Learning Process