Courses, Stanford Online

Stanford CS229 Machine Learning | Spring 2026

17 lectures, 20 hr 36 min in all

This playlist features lectures from the Stanford graduate course CS229 Machine Learning. Learn from the latest CS229 graduate curriculum — now built into XCS229 Machine Learning, our professional education version. Starts November 16, 2026. Enroll now. 🔗 https://stanford.io/xcs229-261116 The graduate course, CS229 Machine Learning, provides a broad introduction to machine learning and statistical pattern recognition. Topics include: supervised learning (generative learning, parametric/non-parametric learning, neural networks); unsupervised learning (clustering, dimensionality reduction); learning theory (bias/variance tradeoffs, practical advice); reinforcement learning and adaptive control. These course lectures discuss recent applications of machine learning, such as to robotic control, data mining, autonomous navigation, bioinformatics, speech recognition, and text and web data processing.