Deep Learning CNN Convolutional Neural Networks with Python - CNN Example

The video tutorial explains the construction of a simple convolutional neural network (CNN) for grayscale images. It covers the setup of convolutional layers with filters, the application of ReLU nonlinearity, and the use of max pooling. The tutorial also discusses flattening the output for a fully connected layer with a softmax function and defines a squared loss function. Finally, it introduces backpropagation and weight updates, emphasizing the potential to extend these concepts to larger networks.

What is the result of applying Max Pooling to the feature map C1?

What is the final output of the convolutional neural network before applying the softmax layer?

How is the loss function defined in the example?