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Neural Networks with Keras Cookbook

You're reading from   Neural Networks with Keras Cookbook Over 70 recipes leveraging deep learning techniques across image, text, audio, and game bots

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Product type Paperback
Published in Feb 2019
Publisher Packt
ISBN-13 9781789346640
Length 568 pages
Edition 1st Edition
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Authors (2):
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V Kishore Ayyadevara V Kishore Ayyadevara
Author Profile Icon V Kishore Ayyadevara
V Kishore Ayyadevara
Srinivas Pradeep Srinivas Pradeep
Author Profile Icon Srinivas Pradeep
Srinivas Pradeep
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Toc

Table of Contents (18) Chapters Close

Preface 1. Building a Feedforward Neural Network 2. Building a Deep Feedforward Neural Network FREE CHAPTER 3. Applications of Deep Feedforward Neural Networks 4. Building a Deep Convolutional Neural Network 5. Transfer Learning 6. Detecting and Localizing Objects in Images 7. Image Analysis Applications in Self-Driving Cars 8. Image Generation 9. Encoding Inputs 10. Text Analysis Using Word Vectors 11. Building a Recurrent Neural Network 12. Applications of a Many-to-One Architecture RNN 13. Sequence-to-Sequence Learning 14. End-to-End Learning 15. Audio Analysis 16. Reinforcement Learning 17. Other Books You May Enjoy

Classifying a song by genre

In this case study, we will be classifying a song into one of 10 possible genres. Imagine a scenario where we are tasked to automatically classify the genre of a song without manually listening to it. This way, we can potentially minimize operational overload as far as possible.

Getting ready

The strategy we'll adopt is as follows:

  1. Download a dataset of various audio recordings and the genre they fit into.
  2. Visualize and contrast a spectrogram of the audio signal for various genres.
  3. Perform CNN operations on top of a spectrogram:
    • Note that we will be performing a CNN 1D operation on a spectrogram, as the concept of translation does not apply in the case of audio recordings
  1. Extract features...
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