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Links for Exercises
Jupyter Tutorial
Train the trainer Lecture 04 Exercises (Introspection)
Python for novices
Resources
Terascale Oct 22
Academic Training - Michael Kagan - 2017
Academic Training: Statistics - Glen Cowan - 2011
Michael Kagan in Paestum 2022
Michael Kagan at Collider School 2021
Francois Fleuret
Gilles Louppe
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Videos
Maurizio Pierini@GGI
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github
Eilam Gross
Introduction to Deep Learning
MIT 6.S191
Deep Learning for Computer Vision
Stanford CS231n
Modern Machine Learning for LHC physicists
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Tutorials
Older Links
Shlomi et al., GNN
Andrew Ng
Luca Lista
2nd Action Plan ErUM-Data Community Meeting
Florian Marquardt auf YouTube
FM
Handwriting Classification
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Mehta et al.
Phys. Rept. 810 (2019) 1-124
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Hastie, Tibshirani, Friedman
The Elements of Statistical Learning, 2nd edition
Murphy
Probabilistic Machine Learning
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An Introduction
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Advanced Topics
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Exercises/Figures
Goodfellow, Bengio and Courville,
Deep Learning
James, Witten, Hastie and Tibshirani,
An Introduction to Statistical Learning
Geron,
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow
Living Review HEP in ML
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git
Zhang, Lipton, Li, and Smola,
Dive into Deep Learning
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