representations and hierarchy

Deep learning gets smarter by learning internal representations that reduce prediction error: data flows forward to produce an output, a loss measures the gap to the target, and gradients flow backward to update millions or billions of parameters so the model’s future guesses improve.​ Forward pass and loss Backpropagation and gradient descent Why depth helps … Read more