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Hands-On Machine Learning with IBM Watson

You're reading from   Hands-On Machine Learning with IBM Watson Leverage IBM Watson to implement machine learning techniques and algorithms using Python

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Product type Paperback
Published in Mar 2019
Publisher Packt
ISBN-13 9781789611854
Length 288 pages
Edition 1st Edition
Languages
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Author (1):
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James D. Miller James D. Miller
Author Profile Icon James D. Miller
James D. Miller
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Toc

Table of Contents (15) Chapters Close

Preface 1. Section 1: Introduction and Foundation
2. Introduction to IBM Cloud FREE CHAPTER 3. Feature Extraction - A Bag of Tricks 4. Supervised Machine Learning Models for Your Data 5. Implementing Unsupervised Algorithms 6. Section 2: Tools and Ingredients for Machine Learning in IBM Cloud
7. Machine Learning Workouts on IBM Cloud 8. Using Spark with IBM Watson Studio 9. Deep Learning Using TensorFlow on the IBM Cloud 10. Section 3: Real-Life Complete Case Studies
11. Creating a Facial Expression Platform on IBM Cloud 12. The Automated Classification of Lithofacies Formation Using ML 13. Building a Cloud-Based Multibiometric Identity Authentication Platform 14. Another Book You May Enjoy

Summary

In this chapter, we introduced and discussed collecting and using biometric data in a biometric authentication solution, how such a solution works as well as feature extraction (in regard to biometric data solutions) was the idea of multimodal fusion. Finally, we expanded the expression detection and analysis solution from Chapter 8, Creating a Facial Expression Platform on IBM Cloud, again using the IBM Watson Visual Recognition service, to create a working biometric authentication solution proof of concept.

The next chapter concludes this book with an overview of what we have covered. The chapter will also shed some light on some of the practical considerations related to developing machine learning systems on the cloud with IBM Watson Studio.

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