Deep Learning with PyTorch (Manning)
Wednesday, 26 August 2020

This book shows how to use PyTorch for deep learning projects.  Authors.Eli Stevens, Luca Antiga and Thomas Viehmann show how to create neural networks and deep learning systems with PyTorch. This practical book quickly gets you to work building a real-world example from scratch: a tumor image classifier. Along the way, it covers best practices for the entire DL pipeline, including the PyTorch Tensor API, loading data in Python, monitoring training, and visualizing results. After covering the basics, the book moves on to larger projects, and the centerpiece of the book is a neural network designed for cancer detection.

 

Author: Eli Stevens, Luca Antiga and Thomas Viehmann
Publisher: Manning
Date: August 2020
Pages: 520
ISBN: 978-617295263
Print: 1617295264
Audience: Python developers
Level: Intermediate
Category: Python and Artificial Intelligence

pytorchdeep

 

  • Training deep neural networks
  • Implementing modules and loss functions
  • Utilizing pretrained models from PyTorch Hub
  • Exploring code samples in Jupyter Notebooks

 

For recommendations of Python books see Books for Pythonistas and Python Books For Beginners in our Programmer's Bookshelf section.

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Learn Quantum Computing with Python and Q#

Author: Dr. Sarah Kaiser and Dr. Chris Granade
Publisher: Manning
Date: June 2021
Pages: 384
ISBN: 978-1617296130
Print: 1617296139
Kindle: B098BNK1T9
Audience: Developers interested in quantum computing
Rating: 4.5
Reviewer: Mike James
Quantum - it's the future...



Visual Complex Analysis

Author:  Tristan Needham
Publisher: Clarendon Press
Pages: 616
ISBN: 978-0198534464
Print: 0198534469
Kindle: B0BNKJTJK1
Audience: The mathematically able and enthusiastic
Rating: 5
Reviewer: Mike James
What's complex about complex analysis?


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