How I Built a Readable AlphaZero From Scratch — A Deep Dive Into the Code

Most AlphaZero repositories fall into one of two traps: they're either so heavily optimised that the algorithm is buried under infrastructure, or they're toy demos that don't actually produce a strong player. I wanted something in the middle — clean enough to read , strong enough to beat you at Gomoku . The result is alphazero-board-games : a lightweight AlphaZero implementation covering Gomoku (9×9 and 15×15) and Connect4, with pretrained checkpoints you can play against immediately. In this post I'm going to pull apart every major component and explain exactly what's happening and why . The Big Picture: What AlphaZero Actually Does Before we touch any code, let's lock down the algorithm at a conceptual level, because there's a lot of confusion in blog posts that conflate AlphaGo, AlphaGoZero, and AlphaZero. AlphaZero (2017) learns entirely from self-play — no human games, no handcrafted features. The training loop has three interlocked components: A residual neural network with two h