Best known materials (for me) that leads to real understanding. These tend to have pretty visualizations and extensive links to related concepts (motivation). Further technical details could be searched elsewhere.
Arrogant sources are generally excluded.
Textbooks are usually contemporary and readable.
- Automatic differentiation
- Betancourt Probability Theory
- Geometric Algebra - Proper math for physics.
- Random matrix theory
- Nyquist-Shannon theorem
- Lecture Notes, UC Merced
- An Introduction to the Conjugate Gradient Method Without the Agonizing Pain
- Algorithms visualization
- Textbook: Kochenderfer and Wheeler. Algorithms for Optimization
- Why Momentum Really Works
- Kevin Murphy's Textbook
- Mathematics for Machine Learning
- Interactive GANs
- Textbook: Kochenderfer, Wheeler, and Wray. Algorithms for Decision Making
- Transformers from Scratch
- Transformers
- Diffusion models
- Probability for Data Science - Effectively the best book I have seen in probability and statistics.
- Textbook, video: McElreath. Statistical Rethinking - Intuitive approach to Bayesian statistics.
- James-Stein paradox
- There are six main narratives of globalisation, all flawed
- Book: Capitalism, Alone - Most reasonable and comprehensive assessment of the current state of affairs.