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Hands-On Machine Learning with IBM Watson

You're reading from  Hands-On Machine Learning with IBM Watson

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

Table of Contents (15) Chapters close

Preface 1. Section 1: Introduction and Foundation
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

Preprocessing faces

We have just mentioned that building a suitable expression database is a lot of work. To be able to build an end-to-end working expression analysis solution (and fit it all into a single chapter of this book), we will take some liberties with our project:

  • We will limit our model's ability to detect and classify only two emotions—happiness and sadness
  • We will supply only a limited amount of expression data to train our model

Obviously, in the real world, our second assumption is a risky one; as in any ML model, less training data typically produces a less valuable result.

Preparing the training data

Again, if we have decided to satisfy only the minimal requirements for using the face model...

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