MiniTorch from Cornell Tech: Build Your Own Mini PyTorch to Master Deep Learning Fundamentals
techNmak · x · 2026-08-20
MiniTorch, developed by Sasha Rush for the Machine Learning Engineering course at Cornell Tech, has 2.4k stars on GitHub.
The idea: build a small Torch-like framework yourself to understand what sits beneath the APIs we normally call without thinking. The accompanying video playlist covers numerical derivatives, autodifferentiation, computation graphs, the chain rule, backpropagation, neural networks, tensors and tensor functions, shapes, gradients, plus tensor and GPU puzzles.
The full course goes further into broadcasting, parallel tensor operations, matrix multiplication, CUDA, convolutions, pooling, softmax, dropout, CNNs, MNIST and sentiment classification. You write the implementation, run tests and debug as you go, with autograded modules (0–4 plus quizzes) via GitHub Classroom. Great for Python-ready learners who want stronger DL fundamentals.
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