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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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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

Speech recognition

In the past few decades, there has been a tremendous amount of research on leveraging deep learning for speech-related applications. Speech recognition has become a part of many day-to-day applications, such as our phones, smartwatches, homes, games, and many more.

It's being implemented as a salient feature in many voice search applications such as Siri and Alexa by tech giants such as Apple and Amazon, respectively. Sound waves are time-domain signals, which means that when we plot a sound wave, one of the axes is time (independent variable) and the other is the amplitude of the wave (dependent variable).

To create a digital recording of the sound wave, we convert the analog sound signal into a digital form by performing sampling. Sampling converts the analog audio signal into a digital signal by taking measurements of the dependent variable...

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