stared/thinking-in-tensors-writing-in-pytorch

Thinking in tensors, writing in PyTorch (a hands-on deep learning intro)

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This hands-on introduction helps you understand the mathematical ideas behind deep learning by showing how they translate directly into PyTorch code. It provides explicit, minimalistic examples in Jupyter Notebooks, going from foundational math equations to practical, working PyTorch implementations. This resource is for students, researchers, or anyone seeking a deeper understanding of deep learning's mathematical underpinnings.

395 stars. No commits in the last 6 months.

Use this if you want to learn the core mathematical concepts of deep learning side-by-side with their implementation in PyTorch.

Not ideal if you're looking for a high-level, abstract introduction to deep learning or a project that doesn't involve coding.

deep-learning-education neural-networks machine-learning-foundations pytorch-training mathematical-modeling
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 16 / 25

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Stars

395

Forks

43

Language

Jupyter Notebook

License

MIT

Last pushed

Jan 10, 2025

Commits (30d)

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