3rd Terascale School of Machine Learning (Part 1: basic introduction)
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Europe/Berlin
Description
The school aims at PhD students and young postdocs, and offers a basic introduction to machine learning. Specifically, three main topics will be discussed:
- The predictive modeling pipeline
- Selecting the best model
- Evaluating model performance
In addition to the lectures, several hands-on tutorials based on Scikit Learn will be offered.
In order to participate successfully in the school, we expect the following prerequisites:
- Basic knowledge of Python programming : defining variables, writing functions, importing modules.
Some prior experience with the NumPy, pandas and Matplotlib libraries is recommended but not required.
For a quick introduction on these requirements, you can go through these course materials or use the following resources:
Registration is now open - registration deadline: 13 July!
The school is supported by the Excellence Cluster Quantum Universe Hamburg.
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