DeepLearningForPhysicsResearchBook/deep-learning-physics
This project contains additional material for the textbook Deep Learning for Physics Research by Martin Erdmann, Jonas Glombitza, Gregor Kasieczka, and Uwe Klemradt.
This project provides practical exercises for individuals studying deep learning applications in physics. It offers hands-on problems that complement the 'Deep Learning for Physics Research' textbook, allowing students and researchers to apply theoretical knowledge to real physics data and simulations. The material is designed for physics students, researchers, and academics looking to enhance their deep learning skills relevant to their field.
Use this if you are a physics student or researcher seeking practical exercises to apply deep learning concepts specifically within a physics context.
Not ideal if you are looking for a general introduction to deep learning or exercises unrelated to physics research applications.
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26
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Jupyter Notebook
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Last pushed
Mar 06, 2026
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