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The Notebook
AI Notebook
I prepared these notes for myself to understand core AI concepts easily. I find it easier when maths is accompanied by visual examples. So I drafted these with Claude and then went through each one to fix the parts that were wrong or unclear.
4
Topics
16
Posts
~375m
Total Read
Topics
LLM
Transformer internals and the ideas that make large language models work. Attention, positional encoding, …
Reinforcement Learning
Policy gradients, value-based methods, and the full post-training pipeline. PPO, DPO, GRPO, Q-learning, and …
Deep Learning
The mechanics underneath every training run. Optimizers, loss landscapes, gradient flow, and the tricks that …
Generative Modeling
How to build models that generate. Diffusion from first principles — DDPM, score matching, SDEs, DDIM — and …