Physics 7097 "Machine Learning"
(Updated for Spring 2021)
Main books (required)
A. Geron,
Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow
.
Jake VanderPlas,
Python Data Science Handbook
(free).
F. Chollet,
Deep Learning with Python
(
new edition
expected in Summer 2021).
Other relevant books (recommended)
P. Bruce and A. Bruce,
Practical Statistics for Data Scientists
.
D. Foster,
Generative Deep Learning
.
A. Trask,
Grokking Deep Learning
.
Even more books (free)
Recently Springer released a number of
Machine Learning and Data books
for free.
T. Hastie, R. Tibshirani, J. Friedman,
The Elements of Statistical Learning
(free)
M. Nielsen,
Neural Networks and Deep Learning
(free online book)
I. Goodfellow, Y. Bengio and A. Courville,
Deep Learning
(free).
J. Patterson and A. Gibson,
Deep learning: A Practitioner's Approach
(very inexpensive).
Python resources
Jake VanderPlas,
A whirlwind tour of python
The
python tutorial
at python.org.
Some relevant arXiv articles
Mehta et al.,
Introduction to Machine Learning for physicists
Jared Kaplan
's notes on
Contemporary Machine Learning for Physicists
Carleo et al.,
Machine learning and the physical sciences
D. Bourilkov,
Machine and Deep Learning Applications in Particle Physics
K. Albertsson et al.,
Machine Learning in High Energy Physics Community White Paper
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