Introduction to Machine Learning
Electronic textbook
Introduction
This electronic textbook develops the course ideas through explanations, derivations, practical details, worked examples, references and optional exercises. Weeks 01–07 are available in English and Russian. Each chapter links to its companion language. Figures, images and animations retain their original labels.
Available chapters
- Week 01 · From a Learning Problem to a Fitted Model
- Week 02 · From Scores to Probabilities and Decisions
- Week 03 · From Local Decisions to Ensembles
- Week 04 · Learning Nonlinear Representations: Feedforward Networks and Backpropagation
- Week 05 · Visual Representation Learning: Local Patterns, Shared Weights, and Convolutional Networks
- Week 06 · Sequential Representation Learning: From Recurrent Memory to Transformer Encoders
- Week 07 · Learning from Evidence: Likelihood, Bayesian Inference, and Latent Variables
Chapter drafts
- Week 10 · Discovering Structure with Unsupervised Learning — introduction, illustrated PCA section, and later chapter outline; instructor review pending. English only.
Return to the course website.