Which Deep Learning Package is Best for Computational Physics?

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SUMMARY

The discussion centers on selecting the best deep learning package for computational physics, specifically for condensed matter applications. Recommendations include PyTorch, TensorFlow, and MxNet, with an emphasis on foundational knowledge in machine learning (ML) and deep learning (DL). Key resources mentioned are "The 100 Page Book on ML" by Burkiv and "Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow" by Aurélien Géron, which provide essential insights into data cleaning and project templates. These resources are crucial for beginners aiming to implement deep learning techniques effectively.

PREREQUISITES
  • Basic understanding of machine learning concepts
  • Familiarity with Python programming
  • Knowledge of data cleaning techniques
  • Awareness of deep learning frameworks like TensorFlow and PyTorch
NEXT STEPS
  • Read "The 100 Page Book on ML" by Burkiv
  • Study "Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow" by Aurélien Géron
  • Explore PyTorch documentation for practical applications
  • Investigate MxNet tutorials for deep learning in computational physics
USEFUL FOR

Researchers in computational physics, data scientists, and anyone interested in applying deep learning techniques to condensed matter physics.

Photonico
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Hi mates,

I am working in computational physics for condensed matter. I have noticed that there are already some articles using deep learning for computational physics. I want to try this method but I do not have any experience with deep learning or machine learning. The first question is that there are many packages for deep learning, such as PyTorch, TensorFlow, and MxNet. Could I get some recommendations about the choice of deep learning packages?Lu
 
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It would seem you really need to step back a bit and read a couple of books on ML and DL.

The 100 page Book on ML by Burkiv is a good start as is the Hands-on book by Geron

http://themlbook.com/

https://www.amazon.com/dp/1098125975/?tag=pfamazon01-20

The hands-on book has a project template at the end and talks about cleaning your data which is an important aspect of ML and DL.

Both books cover the various strategies and the core packages in Python and Tensorflow.
 
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