Understanding machine learning by building it from scratch.
Intro - What is ML
A brief overview of the goals of ML and this blog
Gradient Descent
The most important math behind ML
Optimizing the Math
Reducing computation times using neat stuff
Transformers
The largest paradigm shift in the field
LLM Inference
Improving token throughput at scale