Stanford University • Academic Benchmark
Stanford CS229: Machine Learning
Taught by Prof. Andrew Ng • Stanford Engineering Everywhere
Mathematical Rigor: 60%
Hands-on Code: 40%
The definitive graduate-level introduction to statistical machine learning, covering supervised learning (GLMs, kernels), unsupervised clustering, and reinforcement learning with formal proofs.
Capstone Deliverable: Implement generalized linear models, support vector machines, and GDA from scratch using raw matrix algebra without scikit-learn.