Building Quickgrad

2026

Notes on building a small automatic differentiation engine from first principles.

Quickgrad is a lightweight automatic differentiation and backpropagation engine written in C++.

The project focuses on making the mechanics of neural network training explicit: forward passes, dynamic computational graphs, gradients, and parameter updates. It is intentionally small enough to inspect, but complete enough to train deep neural networks.