CNN_for_MNIST_Handwritten_Digit_Classification
The task of the assignment 3 is the design of a CNN architecture and its training.
Input dataset: MNIST digits (input size: 28x28x1, number of classes: 10).
The CNN has to be designed with the aim of reaching the maximum possible accuracy on the test set, with the hard constraint of a maximum of 7K learnable parameters.