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Deep Learning with R Cookbook

You're reading from   Deep Learning with R Cookbook Over 45 unique recipes to delve into neural network techniques using R 3.5.x

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Product type Paperback
Published in Feb 2020
Publisher Packt
ISBN-13 9781789805673
Length 328 pages
Edition 1st Edition
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Authors (3):
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Swarna Gupta Swarna Gupta
Author Profile Icon Swarna Gupta
Swarna Gupta
Rehan Ali Ansari Rehan Ali Ansari
Author Profile Icon Rehan Ali Ansari
Rehan Ali Ansari
Dipayan Sarkar Dipayan Sarkar
Author Profile Icon Dipayan Sarkar
Dipayan Sarkar
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Toc

Table of Contents (11) Chapters Close

Preface 1. Understanding Neural Networks and Deep Neural Networks 2. Working with Convolutional Neural Networks FREE CHAPTER 3. Recurrent Neural Networks in Action 4. Implementing Autoencoders with Keras 5. Deep Generative Models 6. Handling Big Data Using Large-Scale Deep Learning 7. Working with Text and Audio for NLP 8. Deep Learning for Computer Vision 9. Implementing Reinforcement Learning 10. Other Books You May Enjoy

To get the most out of this book

A good understanding of machine learning and strong knowledge of R is necessary for this book.

Download the example code files

You can download the example code files for this book from your account at www.packt.com. If you purchased this book elsewhere, you can visit www.packtpub.com/support and register to have the files emailed directly to you.

You can download the code files by following these steps:

  1. Log in or register at www.packt.com.
  2. Select the Support tab.
  3. Click on Code Downloads.
  4. Enter the name of the book in the Search box and follow the onscreen instructions.

Once the file is downloaded, please make sure that you unzip or extract the folder using the latest version of:

  • WinRAR/7-Zip for Windows
  • Zipeg/iZip/UnRarX for Mac
  • 7-Zip/PeaZip for Linux

The code bundle for the book is also hosted on GitHub at https://github.com/PacktPublishing/Deep-Learning-with-R-CookbookIn case there's an update to the code, it will be updated on the existing GitHub repository.

We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!

Download the color images

Conventions used

There are a number of text conventions used throughout this book.

CodeInText: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "In step 1, we imported the fashion MNIST data using the dataset_fashion_mnist() function and checked the dimensions of its training and testing partitions."

A block of code is set as follows:

fashion <- dataset_fashion_mnist()
x_train <- fashion$train$x
y_train <- fashion$train$y
x_test <- fashion$test$x
y_test <- fashion$test$y

Bold: Indicates a new term, an important word, or words that you see onscreen. For example, words in menus or dialog boxes appear in the text like this. Here is an example: "Go to Anaconda Navigator from the Start menu."

Warnings or important notes appear like this.
Tips and tricks appear like this.
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