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๐Ÿ€ Challenge: Backpropagation - 3 Layered Neural Network

Explore how to implement backpropagation in a three-layer neural network to compute gradients of the cross-entropy loss function. Understand how to update weights and biases through backpropagation while working on a letter classification task.

Problem statement

Code the backpropagation operation for the three layered neural network to compute the gradient of the cross-entropy loss function with respect to weights and biases of the neural network.

The cross entropy loss function is as follows:

L(y,s)=โˆ‘i=1cyiโ‹…log(si)\mathcal{L}(y, s) = \sum_{i=1}^{c} y_i \cdot log(s_i) ...