A Reverse-Mode Automatic Differentiation Engine
Built a reverse-mode automatic differentiation engine from scratch on top of NumPy — the computational-graph core that powers frameworks like PyTorch and TensorFlow — then used it to train a logistic regression classifier end-to-end.
Python NumPy Autodiff
Overview
A reverse-mode automatic differentiation engine, implemented from scratch on top of NumPy. This is the same core mechanism — building a computational graph of tensor operations and running backpropagation over it — that underlies frameworks like PyTorch and TensorFlow. I used the finished engine to train a logistic regression classifier end-to-end, verifying that gradients computed through the graph actually drive a real model to converge.
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