Into the heart of Multi-Layer Perceptron Neural Networks (Part-2)

Previously, in Part - 1, we completed a forward pass through one neuron and computed the output value. $$\hat{Y} = tanh(w_1x_1 + w_2x_2 + b)$$Now, we will calculate the gradients of parameters [w1, w2, b] using backpropagation. What is Backpropagatio...