conducts EDA on a high-energy physics dataset for Higgs boson decay classification
This project drew heavy inspiration from the work of Peter Sadowski and Daniel Whiteson in their insightful paper "Searching for Higgs Boson Decay Modes with Deep Learning" [1]. You can access the paper here: https://papers.nips.cc/paper_files/paper/2014/file/e1d5be1c7f2f456670de3d53c7b54f4a-Paper.pdf.
The script was working with data that originated from the Large Hadron Collider (LHC) ATLAS experiment, courtesy of the Learning to Discover: The Higgs Boson Machine Learning Challenge [2]. The dataset boasted a massive 250,000 events, each packed with details about particle collisions.