Machine Learning for Fundamental Physics School (ML4FP) 2025

Prerequisites

Python:

It is absolutely necessary that you are familiar with Python. We strongly recommend you to go through the basics (eg. numpy, matplotlib) if you do not use python frequently.

• Go through the python.ipynb, numpy.ipynb, matplotlib.ipynb notebooks of this tutorial: https://github.com/maxnoe/scientific_python_notebooks
• A more detailed tutorial (optional): https://swcarpentry.github.io/python-novice-inflammation/01-intro.html

 

ML packages: PyTorch, Tensorflow, SKLearn

It will be worthwhile to familiarize yourself with common ML tools like PyTorch, Tensorflow and SKLearn prior to the school. We will introduce these on the first day and then use them for more advanced tutorials on the subsequent days. Have a better familiarity with these tools will make the advanced tutorials easier to follow.

PyTorch

• PyTorch tutorials: https://pytorch.org/tutorials/
• PyTorch video lecture: Deep Learning With PyTorch - Full Course

TensorFlow

• Tutorials: https://www.tensorflow.org/tutorials
• TensorFlow + Keras video lecture: TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

 

LXPlus Account:

ATLAS experiment members would need a working LXPlus account for optional exercises on the final day