The Higgs boson is an elementary particle in the Standard Model of physics which explains why other particles have mass. Its discovery at the Large Hadron Collider at CERN was announced in March 2013. In this project, you will apply machine learning techniques to actual CERN particle accelerator data to recreate the process of “discovering” the Higgs particle. For some background, physicists at CERN smash protons into one another at high speeds to generate even smaller particles as by-products of the collisions. Rarely, these collisions can produce a Higgs boson. Since the Higgs boson decays rapidly into other particles, scientists don’t observe it directly, but rather measure its“decay signature”, or the products that result from its decay process. Since many decay signatures look similar, it is our job to estimate the likelihood that a given event’s signature was the result of a Higgs boson (signal) or some other process/particle (background).
The dataset can be found here: https://www.kaggle.com/competitions/higgs-boson/data