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Applying Machine Learning in CERN experiments

Here I have done a chain of mini-projects to infer from the data that was generated by CERN. I have used several machine learning algorithms depending upon the type of data and the type of inference we want to make.

Each of the project has been explained with a seperate readme and the proper visualization and everything is done inside the jupyter notebooks to understand the essence of what I did in each one of the projects.

Project Name Description Notebook
Z-Boson mass measurement Computing the mass of Z-boson
Particle Identification Identify the type of atomic/subatomic particle
Search for rare decay To find the evidence of rare decay
Searching for electromagnetic showers Develop a model identifying basetracks of electronic magnetic showers
Detector Optimization Improve the conventional tracking systems using gaussian process

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