3rd Terascale School of Machine Learning (Part 1: basic introduction)

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:

• Introduction to Python

• Introduction to NumPy

• Introduction to Pandas

• Introduction to Matplotlib

Registration is now open - registration deadline: 13 July!

The school is supported by the Excellence Cluster Quantum Universe Hamburg.