Stanford CS229 Machine Learning, taught at Stanford by Andrew Ng, is one of the best-known courses in the field. The 2018 lecture videos are on Stanford Online’s YouTube channel, and the lecture notes and problem sets are free at cs229.stanford.edu.
What’s in it? Linear and logistic regression, support vector machines, decision trees and ensemble methods, neural networks, model selection and cross-validation, independent component analysis (ICA) and reinforcement learning.
Why we recommend it: The maths behind the methods whose intuition we covered in our SVM, Random Forest and XGBoost posts is derived here step by step. There’s also a lecture on ICA, which we use to clean artefacts from EEG.
Who is it for? Anyone with probability, linear algebra and calculus who wants machine learning to stop being a black box. It’s a maths-heavy course.
- Course page: Stanford CS229