Useful ML Courses and Blogs

Blogs

1. Machine Learning Blog — CMU
2. Berkeley Artificial Intelligence Research (BAIR) Blog
3. Stanford AI Blog
4. Lilian Weng's Blog on RL — one of the best resources for clear, deep RL writeups
5. DeepMind Blog

Courses and Lecture Series

1. Create Machine Learning Models — Microsoft
2. Stanford CS229: Machine Learning — Andrew Ng
   • Linear Regression and Gradient Descent
   • Logistic Regression, Naive Bayes, SVMs, Kernels
   • Decision Trees, Neural Networks, Debugging ML Models
3. Machine Learning Crash Course — Google
4. Introduction to Machine Learning for Coders — Jeremy Howard (fast.ai)
5. Foundations of Machine Learning — Bloomberg ML EDU
6. Tabular Data — Machine Learning University (Amazon)
7. Stat 451: Intro to Machine Learning — Sebastian Raschka
8. DeepMind × UCL: Reinforcement Learning
9. NYU Deep Learning SP21 — Yann LeCun & Alfredo Canziani
   • Neural Nets: rotation and squashing
   • Latent Variable Energy Based Models
   • Unsupervised Learning, GANs, Autoencoders