Neural Networks

The architecture itself — weights, layers, activations, and the search that sets them.

3 articles, newest first.

• Neural networks · Part 22 of 33 · 7 min Backpropagation explained plainly How a network works out which weight was to blame for a wrong answer, why the chain rule is really credit assignment, and why backprop is bookkeeping rather than magic.
• Neural networks · Part 21 of 33 · 6 min Gradient descent from first principles The cost surface, why the gradient points uphill, what the learning rate really controls, and why local minima matter far less in practice than everyone expects.
• Neural networks · Part 20 of 33 · 7 min What a neural network actually is Layers, weights, biases and activations built up from scratch on the handwritten-digit problem, and why "learning" means nothing more exotic than adjusting a pile of numbers.