Machine Learning
Free, no sign-up neededArchived courseEnglish
About this course
This course provides a broad introduction to machine learning and statistical pattern recognition. Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (clustering, dimensionality reduction, kernel methods); learning theory (bias/variance tradeoffs; VC theory; large margins); reinforcement learning and adaptive control.
Description from Stanford Engineering Everywhere.
Where to take this course
- Open Stanford Engineering Everywhere (new tab)Stanford Engineering Everywhere · Archived course