Convolutional Neural Networks for Beginners using Keras and TensorFlow 2

The number of parameters of the conv2D layer corresponds to the weight matrix W of 5 5 and a b bias for each of the filters is 832 parameters (32 (25 1)). Max-pooling does not require parameters since it is a mathematical operation to find the maximum. And in order to build a "deep" neural network, we can stack several layers like the one built in the previous section. To show the reader how to do it in our example, we will create a second group of layers that will have 64 filters with a 5 5 window in the convolutional layer and a 2 2 window in the pooling layer.