Educational material for the machine learning and deep learning tutorial course. In this course, we want to cover the following topics:
- introduce the foundations of machine learning (ML) and deep learning (DL)
- introduce the deep neural network as one model class inside the supervised learning paradigm
- provide an overview of existing Python-based libraries that target deep learning workloads
- delve into PyTorch as a framework
- implement a solution to a toy deep learning problem
- set up data loading
- implement multiple toy models
- write the core training loop and watch our network learn :)
- Colab Session: Handson: Implement Network
- Colab Session: Data set loading and transformation introduction with Fashion MNIST
- Colab Session: Training loop and learning