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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

Product type Paperback

Published in Mar 2019

Publisher Packt

ISBN-13 9781789611854

Length 288 pages

Edition 1st Edition

Languages

Python

Tools

IBM Watson

Concepts

Machine Learning

Author (1):

James D. Miller

View More author details

Table of Contents (15) Chapters

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

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Who this book is for

This book is aimed at data scientists and machine learning engineers who would like to get introduced to IBM Cloud and its machine learning services using practical examples.

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Authors (1)

James D. Miller

James D. Miller

James D. Miller is an IBM certified expert, Master Consultant, Application/System Architect with +35 years of applications & system design/development experience across multiple platforms, technologies and data formats, including Big Data. His experience includes IBM Planning Analytics, BI, Web architecture & design, systems analysis, GUI design & testing, Data modeling, design, and development of OLAP, Client/Server, Web & Mainframe applications and systems utilizing: Planning Analytics Workspace (PAW), IBM Watson Analytics, Cognos BI & TM1, Framework Manager, dynaSight/ArcPlan, ASP, DHTML, XML, MS Visual Basic, VBA, PERL, R, SPLUNK, MS SQL Server, ORACLE, etc. He has authored numerous books, including Implementing Splunk - Second Edition; Mastering Splunk; Hands-On Machine Learning with IBM Watson; IBM Watson Projects; Statistics for Data Science; Mastering Predictive Analytics with R - Second Edition and others. Project areas include those with Data Analytics, Planning Analytics, and FOPM projects, holding various roles from architect, developer, technical and project leader.

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