Notes on ML, DL, NLP & LLM Systems
Structured tracks on the math, models, and systems behind modern machine learning.
Math Foundations
The probability, statistics, and linear algebra that underpin every model in this site.
4 lessons →Machine Learning
Core supervised and unsupervised methods, and how to tell if a model actually works.
4 lessons →Deep Learning
Neural networks from the first layer to the architectures that power modern vision and language models.
4 lessons →NLP
Turning text into something a model can learn from, from tokenization to full language models.
4 lessons →LLM Systems
Evaluating, serving, and understanding large language models in production.
4 lessons →