Resources

The standard reference for the mathematical and conceptual foundations of deep learning. Dense, but the only book that covers everything in one place.

Karpathy builds neural networks from scratch in plain Python and PyTorch, ending with a working transformer trained on Tiny Shakespeare.

Gilbert Strang's full MIT 18.06 course. The single best place to learn linear algebra well enough to read ML papers without flinching.