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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

Introduction to IBM Cloud

In this chapter, we will provide a brief introduction to the IBM Cloud platform and the services that it offers, such as machine learning (ML). Moreover, this chapter will provide detailed instructions on how to set up a data science and machine learning development environment on the IBM Cloud. Finally, we will conclude with a project example that involves loading and visualizing data.

We'll break down this first chapter into the following sections:

  • Understanding IBM Cloud
  • The IBM Cloud and Watson Machine Learning services
  • Setting up the environment
  • Data visualization tutorial
You have been reading a chapter from
Hands-On Machine Learning with IBM Watson
Published in: Mar 2019
Publisher: Packt
ISBN-13: 9781789611854
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