Machine learning with Python
with Dr. Alexander Britz and Dr. Ilona Lipp
Date: 11, 14 +15 October 2024 9 am - 4 pm
Venue: 11 Oct: online | 14 + 15 Oct: Room 108, building 35 | DESY (see here for directions)
Credit points: 1.5
Prerequisite for the participation in this workshop is intermediate programming knowledge in Python and/or the previous successful participation in a Python basics course such as this one (or equivalent skills). Without sufficient programming knowledge, participation is not recommended.
Workshop outline:
In the workshop “Machine Learning with Python” the participants learn the fundamentals of implementing machine learning algorithms with Python and Jupyter Notebooks. The workshop consists of a series of modules, each having a lecture and exercise part. The specific content of the course is:
- Introduction to general concepts of machine learning
- Data preparation for machine learning
- Selected advanced Python syntax important for machine learning
- Virtual environments and version control with Git & Github
- Supervised learning with Scikit-learn
- Neural networks and deep learning with PyTorch
- Outlook: Unsupervised and reinforcement learning algorithms
As a pre-requisite, the participants should have a basic knowledge of Python, e.g. as acquired in a “Python basics” course.
