Neural net in PyTorch - Backprop (Theory)

This video includes an depth explanation of the backpropagation algorithm and its working. Here we compute all the derivatives of the loss used in backprop, from scratch. Computing the derivatives from scratch helps to understand how the machine learning model actually learns by minimizing the loss.
This video includes the under-the-hood working of PyTorch neural net layers.
Hope you all enjoy the maths involved over here.
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