Hyatt Saleh - The Deep Learning with PyTorch Workshop: Build deep neural networks and artificial intelligence applications with PyTorch
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- Book:The Deep Learning with PyTorch Workshop: Build deep neural networks and artificial intelligence applications with PyTorch
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The Deep Learning with PyTorch Workshop: Build deep neural networks and artificial intelligence applications with PyTorch: summary, description and annotation
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Get a head start in the world of AI and deep learning by developing your skills with PyTorch
Key Features- Learn how to define your own network architecture in deep learning
- Implement helpful methods to create and train a model using PyTorch syntax
- Discover how intelligent applications using features like image recognition and speech recognition really process your data
Want to get to grips with one of the most popular machine learning libraries for deep learning? The Deep Learning with PyTorch Workshop will help you do just that, jumpstarting your knowledge of using PyTorch for deep learning even if youre starting from scratch.
Its no surprise that deep learnings popularity has risen steeply in the past few years, thanks to intelligent applications such as self-driving vehicles, chatbots, and voice-activated assistants that are making our lives easier. This book will take you inside the world of deep learning, where youll use PyTorch to understand the complexity of neural network architectures.
The Deep Learning with PyTorch Workshop starts with an introduction to deep learning and its applications. Youll explore the syntax of PyTorch and learn how to define a network architecture and train a model. Next, youll learn about three main neural network architectures - convolutional, artificial, and recurrent - and even solve real-world data problems using these networks. Later chapters will show you how to create a style transfer model to develop a new image from two images, before finally taking you through how RNNs store memory to solve key data issues.
By the end of this book, youll have mastered the essential concepts, tools, and libraries of PyTorch to develop your own deep neural networks and intelligent apps.
What you will learn- Explore the different applications of deep learning
- Understand the PyTorch approach to building neural networks
- Create and train your very own perceptron using PyTorch
- Solve regression problems using artificial neural networks (ANNs)
- Handle computer vision problems with convolutional neural networks (CNNs)
- Perform language translation tasks using recurrent neural networks (RNNs)
This deep learning book is ideal for anyone who wants to create and train deep learning models using PyTorch. A solid understanding of the Python programming language and its packages will help you grasp the topics covered in the book more quickly.
Table of Contents- Introduction to Deep Learning and PyTorch
- Building Blocks of Neural Networks
- A Classification Problem Using DNNs
- Convolutional Neural Networks
- Style Transfer
- Analyzing the Sequence of Data with RNNs
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Build deep neural networks and artificial intelligence applications with PyTorch
Hyatt Saleh
Copyright 2020 Packt Publishing
All rights reserved. No part of this course may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.
Every effort has been made in the preparation of this course to ensure the accuracy of the information presented. However, the information contained in this course is sold without warranty, either express or implied. Neither the author, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this course.
Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this course by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.
Author: Hyatt Saleh
Reviewers: Tim Hoolihan, Narinder Kaur Saini, Anuj Shah, Nahar Singh, and Subhash Sundaravadivelu
Managing Editor: Anush Kumar Mehalavarunan
Acquisitions Editors: Royluis Rodrigues, Kunal Sawant, Sneha Shinde, Anindya Sil, and Karan Wadekar
Production Editor: Shantanu Zagade
Editorial Board: Megan Carlisle, Samuel Christa, Mahesh Dhyani, Heather Gopsill, Manasa Kumar, Alex Mazonowicz, Monesh Mirpuri, Bridget Neale, Dominic Pereira, Shiny Poojary, Abhishek Rane, Brendan Rodrigues, Erol Staveley, Ankita Thakur, Nitesh Thakur, and Jonathan Wray
First published: July 2020
Production reference: 1200720
ISBN: 978-1-83898-921-7
Published by Packt Publishing Ltd.
Livery Place, 35 Livery Street
Birmingham B3 2PB, UK
Thank you for purchasing the print edition of The Deep Learning with PyTorch Workshop. Every physical print copy includes free online access to the premium interactive edition. There are no extra costs or hidden charges.
Figure A: An example of the companion video in the Workshop course player (dark mode)
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