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

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

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