Deep learning and PyTorch

What happens inside a network while it trains, with a loop you write yourself first.

TensorsShape, dtype and device, and why shape is the thing you will print most in your life.
Autogradrequires_grad, the computation graph and backward, step by step.
A training loop by handForward, loss, backward, optimiser step, with no Trainer and no shortcut.
Layers and normalisationLinear, activations, dropout and normalisation, and why each one works.