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Deep Learning with PyTorch

You're reading from Deep Learning with PyTorch

Product type Book

Published in Feb 2018

Publisher Packt

ISBN-13 9781788624336

Pages 262 pages

Edition 1st Edition

Languages

Concepts

Author (1):

Vishnu Subramanian

Table of Contents (11) Chapters

Preface

1. Getting Started with Deep Learning Using PyTorch

2. Building Blocks of Neural Networks

3. Diving Deep into Neural Networks

4. Fundamentals of Machine Learning

5. Deep Learning for Computer Vision

6. Deep Learning with Sequence Data and Text

7. Generative Networks

8. Modern Network Architectures

9. What Next?

10. Other Books You May Enjoy

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Interesting ideas to explore

Most of the concepts that we learned in the book form the foundation of modern applications that are powered by deep learning. In this section, we will look at the different interesting projects that we can do that are related to computer vision and natural language processing (NLP).

Object detection

All the examples we have seen in this book help you in detecting whether a given image is this (cat) or that (dog). But, to solve some of the problems in the real world, you may need to identify different objects in an image, such as shown here:

Output of object detection algorithm

This image shows the output of an object detection algorithm where the algorithm is detecting objects such as a beautiful...

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Authors (1)

Vishnu Subramanian

Vishnu Subramanian has an experience in leading, architecting and implementing several Big Data analytical projects (AI, ML and Deep Learning). Specialized in Machine learning, Deep Learning, Distributed ML, and Visualization. Also, he has experience in domains like Retail, Finance, and Travel and has specialized in understanding and coordinating between Business, AI (Machine Learning, Deep learning) and Engineering teams.

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