A NumPy-based implementation of neural networks from scratch, covering core components like forward and backward propagation, activation functions, loss functions, and optimizers, inspired by the "Neural Networks from Scratch" book.
neural-network numpy regularization learning-by-doing scratch-implementation optimizers dropout-layers indepth
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Updated
Apr 25, 2025 - Python