Backprop in Action

Behind every neural network is an elegant algorithm: backpropagation. Libraries hide it behind a single .fit() call, but today you'll build it yourself. Using only NumPy, you'll create synthetic data, define a sigmoid neuron, initialize weights, and manually implement the forward pass, loss computation, and gradient update. By the end, you'll truly understand how a neural network learns.