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ML Tutorial

These are some hands-on Jupyter notebooks to help beginners start using a selected set of ML methods. When there was no time to delve into the details of the presentation, some extra details on the maths derivations are also given in the notebooks.

Most of the notebooks require installing special software the following is a general setup that should work with most of the given notebooks. The list of packages needed in each given notebook is given in the beginning of the notebook with a !pip install ... command.

pip install torchvision torch pandas numpy matplotlib ipympl torchbnn scikit-learn

All the data used in the examples are produced on-the-fly for demonstration purposes, or are taken from public and open resources. None of the data comes from the EuXFEL, as the purpose of the examples is to show the idea behind the methods.

Contact us at the EuXFEL Data Analysis group at any time if you need help analysing your data!

Danilo Ferreira de Lima: danilo.enoque.ferreira.de.lima@xfel.eu

Arman Davtyan: arman.davtyan@xfel.eu