Forward & Backward Propagation

Summary

Forward propagation computes predictions layer by layer; backward propagation computes gradients layer by layer in reverse — together, the training loop of every neural network.

• 1Trace forward and backward passes by hand on a tiny 2-layer network.
• 2Implement a manual backward pass in NumPy before relying on autograd.
• 3Learn how PyTorch's autograd automates this process under the hood.