Machine-Learning-for-PIs

This is the course page for the course taught at the University of Bonn. The course programme includes four course days covering key concepts in machine learning.

• We recommend reading the Python-Tutorial to get started.

1. Day - Mathematical and Software Engineering foundations

   • a. Intro
   • b. Supervising software projects, software exercise
   • c. Optimization, optimization exercise
   • d. Linear Algebra, algebra exercise
   • e. Statistics

2. Day - Foundations of Machine Learning

   • a. Basics, ML basics exercise
   • b. Support Vector Machines, SVM exercise
   • c. Principal Component Analysis, PCA exercise

3. Day - Convolutional Neural networks

   • a. Feed-Forward Networks, FFN exercise
   • b. Convolutional Neural Networks, CNN exercise
   • c. Segmentation, Segmentation Exercise

4. Day - Interpretable machine learning and Large Language Models

   • a. Interpretable machine learning, interpretable machine learning exercise
   • b. Sequence processing and language models, language models exercise

We thank the state of North Rhine-Westphalia and the Federal Ministry of Education and Research for supporting this project.