Machine Learning

These notes introduce machine learning to people with a background in nuclear physics. They cover (un)supervised learning, neural networks, decision trees, convolutional neural networks, and others. The notes include machine learning exercises for experimental and theoretical nuclear physics topics.

The collected material was presented at the National Nuclear Physics Summer School 2024. The lecture covers AI in a Nutshell how to build your own Machine Learning model and implementation of ML in nuclear physics. The presentations also includes code examples with their explanation.