Uso de técnicas de Machine Learning en el experimento CMS

Experimental Particle Physics is in a golden era full of technological challenges. To overcome them, the substantial collaborations within the LHC (Large Hadron Collider) have implemented Machine Learning techniques in its operations with impressive results. This document summarizes some of the main applications of Automated Machine Learning, particularly of Artificial Neural Networks, in the CMS (Compact Muon Solenoid) experiment. In addition, the importance of collaborative and interdisciplinary work for the correct implementation and interpretation of these analysis techniques is highlighted. The aim of this work is to awaken interest in these topics among the members of Particle Physics and Computer Science communities, in order to enhance the possibilities of joint research projects.