A project-based curriculum that teaches PyTorch by rebuilding it from scratch. Start with scalar backpropagation, create a reverse-mode autodiff engine, expand it into tensors, then implement neural networks, optimizers, CNNs, attention, Transformers, ViTs, and a mini PyTorch framework. Every gradient is code you write and understand.
roiamiel1/Build-Deep-Learning-From-Scratch: A project-based curriculum that teaches PyTorch by rebuilding it from scratch. Start with scalar backpropagation, create a reverse-mode autodiff engine, expand it into tensors, then implement neural networks, optimizers, CNNs, attention, Transformers, ViTs, and a mini PyTorch framework. Every gradient is code you write and understand.
