PHYS 762 Applied Machine Learning in Nuclear and Particle Physics

Credits: 3

This one-semester course introduces problem solving in nuclear and particle physics through statistical inference, machine learning (ML) algorithms, and data mining techniques. The course focuses on the application of state-of-the-art ML methods in physics, such as Monte Carlo sampling, regression and classification techniques, deep learning, dimensionality reduction, and data cleaning.

Prerequisites: PHYS 733 or PHYS 761 or DSE 559

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