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.

<ASIN:1617295264>

 

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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Refactoring JavaScript

Author: Evan Burchard
Publisher: O'Reilly
Date: March 2017
Pages: 422
ISBN: 978-1491964927
Print: 1491964928
Kindle: B06XK1V629
Audience: JavaScript programmers
Rating: 3
Reviewer: Ian Elliot

There is a lot of JavaScript out there that needs refactoring - can this book help?



JavaScript: The New Toys

Author: T.J. Crowder
Publisher: Wrox
Date: July 2020
Pages: 260
ISBN: 978-1119367956
Print: 1119367956
Kindle: B08C9PH74Z
Audience: Experienced JavaScript developers
Rating: 4.5
Reviewer: Mike James
Great title! Can the book be as good?


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