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The Deep Learning with PyTorch Workshop

You're reading from The Deep Learning with PyTorch Workshop

Product type Book

Published in Jul 2020

Publisher Packt

ISBN-13 9781838989217

Pages 330 pages

Edition 1st Edition

Languages

Concepts

Author (1):

Hyatt Saleh

Table of Contents (8) Chapters

Preface

1. Introduction to Deep Learning and PyTorch

2. Building Blocks of Neural Networks

3. A Classification Problem Using DNN

4. Convolutional Neural Networks

5. Style Transfer

6. Analyzing the Sequence of Data with RNNs

Appendix

Natural Language Processing

Computers are good at analyzing standardized data, such as financial records or databases stored in tables. In fact, they are better than humans in doing so as they have the ability to analyze hundreds of variables at a time. On the other hand, humans are great at analyzing unstructured data, such as language, which is something that computers are not great at doing unless they have a set of rules at hand to help them understand it.

With this in mind, the biggest challenge for computers in regard to human language is that, even though a computer can be good at analyzing human language after being trained for a very long time on a very large dataset, they are still unable to understand the real meaning behind a sentence as they are neither intuitive nor capable of reading between the lines.

This means that while humans are able to understand that a sentence that says "He was on fire last night. What a great game!" refers to the performance...

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Authors (1)

Hyatt Saleh

Hyatt Saleh discovered the importance of data analysis for understanding and solving real-life problems after graduating from college as a business administrator. Since then, as a self-taught person, she not only works as a machine learning freelancer for many companies globally, but has also founded an artificial intelligence company that aims to optimize everyday processes. She has also authored Machine Learning Fundamentals, by Packt Publishing.

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