Convolutional Neural Networks (CNN's)

In the following exercises, Convolutional Neural Networks (CNNs) will be used for multiclass classification with the PyTorch library. The objective is to explore CNN architectures, focusing on how network topology and optimization strategies influence performance. The performance of the CNN will be compared to a Multilayer Perceptron (MLP) to determine which architecture is better suited for the Fashion MNIST dataset. Additionally, the concepts of regularization and cross-validation will also be examined.

Learning goals

After this week's exercises, you should be able to:

Experiment with the CNN architecture to better reason about the impact of the different factors involved.
Visually investigate different layers and reason about the effect of different layers on the prediction.
Evaluate the performance and reason about optimization strategies.
Evaluate the performance and reason about tuning techniques.
Evaluate the performance and discuss advantages and limitations.