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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 FREE CHAPTER
2. Introduction to IBM Cloud 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

Building a Cloud-Based Multibiometric Identity Authentication Platform

In this chapter, using IBM Watson Studio, we will walk through the construction of a functioning cloud-based human identification system using biometric traits. We will first introduce biometrics and consider what we mean by biometric data. Then, we will explain the types of preprocessing needed for each biometric. Additionally, we will learn about the process of how to extract meaningful features from biometric data. Lastly, we will cover the concepts behind multimodal data fusion.

The following topics will be covered in this chapter:

  • Understanding biometrics
  • Exploring biometric data
  • Feature extraction
  • Biometric recognition
  • Multimodal fusion
  • Our example
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