This repository holds the codes for the PyTprch examples to be used in the Boot Camp.
For the examples, we will be using the famous MNIST dataset, which is large database of handwritten digits that is commonly used for training various image processing systems.
To showcase the power of convolutional neural networks to handle images, we use the cnn.py scrip. The script objective is to load and train a simple CNN on the MNIST dataset,
with the objective of classify the digits from one to 9.
we also showcase how auto-encoders are able to compress and reconstruct the MNIST data. We show the examples of a AR using MLPs and using CNN which showcase a much more improved performance.