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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Thoughtful Machine Learning with Python

Author: Matthew Kirk
Publisher: O'Reilly
Pages:250
ISBN: 978-1491924136
Print: 1491924136
Kindle:B01N12DLF9
Audience: Non maths oriented programmers wanting to get into machine learning.
Rating: 2
Reviewer: Mike James

A book on AI in Python, what could be better?



SQL Server 2017 Administrators Guide

Author: Marek Chmel & Vladimir Muzny
Publisher: Packt 
Pages: 434
ISBN: 978-1786462541
Print: 1786462540
Kindle: B075V9LQ97
Audience: DBAs and curious devs
Rating: 1.0
Reviewer: Ian Stirk

This book aims to give you the skills to set up, administer, and maintain SQL Server 2017 databases  [ ... ]


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