MNIST dataset includes images of handwritten digits. We used a neural network with $3$ layers to classify the sample data.

Modify the network by including more layers and changing the number of neurons in each layer.

Discuss the impacts of the changes you apply.

Create sample inputs manually and test if they are classified correctly $($use numpy arrays to define new data, and give it as input to the trained model$)$