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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

Data fusion

Data fusion is not a data analysis practice, but rather describes the integration of data from disparate sources. Thankfully, you will find that you can use Watson Studio to collect and combine data sources without much effort.

With Watson Studio, you can set up a catalog for all of your data sources so that you can easily find and share data (and other assets). A catalog is a defined private space within an environment or organization. It is a way to organize your resources across many data science projects—resources such as data assets and analytical assets—and can be used to manage the access that users have to each of these assets.

What is particularly exciting about this feature is the fact that you can organize and control access to many different types of asset within a single catalog including the following:

  • Data in files
  • Connected data
  • Connections...
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