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Python Machine Learning Cookbook

You're reading from   Python Machine Learning Cookbook Over 100 recipes to progress from smart data analytics to deep learning using real-world datasets

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Product type Paperback
Published in Mar 2019
Publisher Packt
ISBN-13 9781789808452
Length 642 pages
Edition 2nd Edition
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Authors (2):
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Giuseppe Ciaburro Giuseppe Ciaburro
Author Profile Icon Giuseppe Ciaburro
Giuseppe Ciaburro
Prateek Joshi Prateek Joshi
Author Profile Icon Prateek Joshi
Prateek Joshi
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Toc

Table of Contents (18) Chapters Close

Preface 1. The Realm of Supervised Learning FREE CHAPTER 2. Constructing a Classifier 3. Predictive Modeling 4. Clustering with Unsupervised Learning 5. Visualizing Data 6. Building Recommendation Engines 7. Analyzing Text Data 8. Speech Recognition 9. Dissecting Time Series and Sequential Data 10. Analyzing Image Content 11. Biometric Face Recognition 12. Reinforcement Learning Techniques 13. Deep Neural Networks 14. Unsupervised Representation Learning 15. Automated Machine Learning and Transfer Learning 16. Unlocking Production Issues 17. Other Books You May Enjoy

Introducing speech recognition

Speech recognition refers to the process of recognizing and understanding spoken language. The input comes in the form of audio data, and the speech recognizers will process this data to extract meaningful information from it. This has a lot of practical uses, such as voice-controlled devices, the transcription of spoken language into words and security systems.

Speech signals are very versatile in nature. There are many variations of speech in the same language. There are different elements to speech, such as language, emotion, tone, noise, and accent. It's difficult to rigidly define a set of rules of what can constitute speech. Even with all these variations, humans are very good at understanding all of this with relative ease. Hence, we need machines to understand speech in the same way.

Over the last couple of decades, researchers have...

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