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Starts with a simple CPU-only implementation to teach the basics, then adds GPU-based training, and finally shows how to scale up to large data by batching your training set to the GPU.
Along the way teaches the basic concepts behind tensors, neural networks, activation functions, forward propagation, loss functions, back propagation, gradient descent, and a very tiny bit of computer vision.
