RENN

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Inspired by Andrej Karpathy’s micrograd, this lecture builds a neural network from scratch, manually deriving gradients, automating backpropagation, and leveraging the TANH activation for nonlinearity. We bridge to PyTorch, demonstrating gradient descent’s power to minimize loss and reveal neural network fundamentals.

ai artificial-intelligence artificial-neural-networks machine-learning neural-network neural-networks neural-networks-from-scratch nn nnfs pytorch

Creat：2024-11-22T08:43:22

Update：2024-11-24T03:00:13

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