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TensorFlow 1.x Deep Learning Cookbook

You're reading from TensorFlow 1.x Deep Learning Cookbook Over 90 unique recipes to solve artificial-intelligence driven problems with Python

Product type Paperback

Published in Dec 2017

Publisher Packt

ISBN-13 9781788293594

Length 536 pages

Edition 1st Edition

Languages

Python

Tools

TensorFlow

Concepts

Deep Learning

Authors (2):

Dr. Amita Kapoor

Antonio Gulli

View More author details

Table of Contents (15) Chapters

Preface

1. TensorFlow - An Introduction FREE CHAPTER

2. Regression

3. Neural Networks - Perceptron

4. Convolutional Neural Networks

5. Advanced Convolutional Neural Networks

6. Recurrent Neural Networks

7. Unsupervised Learning

8. Autoencoders

9. Reinforcement Learning

10. Mobile Computation

11. Generative Models and CapsNet

12. Distributed TensorFlow and Cloud Deep Learning

13. Learning to Learn with AutoML (Meta-Learning)

14. TensorFlow Processing Units

Components of TPUs

Generating music with dilated ConvNets, WaveNet, and NSynth

WaveNet is a deep generative model for producing raw audio waveforms. This breakthrough technology has been introduced (https://deepmind.com/blog/wavenet-generative-model-raw-audio/) by Google DeepMind(https://deepmind.com/) for teaching how to speak to computers. The results are truly impressive and online you can find examples of synthetic voices where the computer learns how to talk with the voice of celebrities, such as Matt Damon.

So, you might wonder why learning to synthesize audio is so difficult. Well, each digital sound we hear is based on 16,000 samples per second (sometimes 48,000 or more) and building a predictive model where we learn to reproduce a sample based on all the previous ones is a very difficult challenge. Nevertheless, there are experiments showing that WaveNet has improved the current state...

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