Stanford's Machine Learning (CS229)

- It's accompanying course materials.

- Also, other significant videos of Computer Science Lectures.

- Supervised Learning, Discriminative Algorithms
- Generative Algorithms
- Support Vector Machines
- Learning Theory
- Regularization and Model Selection
- Online Learning and the Perceptron Algorithm
- Unsupervised Learning, k-means clustering
- Mixture of Gaussians
- The EM Algorithm
- Factor Analysis
- Principal Components Analysis
- Independent Components Analysis
- Reinforcement Learning and Control

- Linear Algebra Review and Reference
- Probability Theory Review
- Convex Optimization Overview, Part I
- Convex Optimization Overview, Part II
- Hidden Markov Models