Machine learning

Abstract

Advanced machine learning techniques have become ubiquitous: from computer vision algorithms found on a plethora of small devices such as cameras or smartphones to the recent rise of tremendously powerful large language models. Also in high energy particle physics, these techniques have become essential and have led to a significant increase in physics reach, from simple feed-forward algorithms used to distinguish signal and background processes to more complex neural networks that utilise the underlying physics structure of the data. This section will cover the basics of neural networks and their training and will then discuss examples of the building blocks that make up modern machine learning algorithms, aiming to provide a tool box for their further application in physics analyses.