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Machine Learning in Java

You're reading from   Machine Learning in Java Helpful techniques to design, build, and deploy powerful machine learning applications in Java

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Product type Paperback
Published in Nov 2018
Publisher Packt
ISBN-13 9781788474399
Length 300 pages
Edition 2nd Edition
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Authors (2):
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Ashish Bhatia Ashish Bhatia
Author Profile Icon Ashish Bhatia
Ashish Bhatia
Bostjan Kaluza Bostjan Kaluza
Author Profile Icon Bostjan Kaluza
Bostjan Kaluza
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Toc

Table of Contents (13) Chapters Close

Preface 1. Applied Machine Learning Quick Start FREE CHAPTER 2. Java Libraries and Platforms for Machine Learning 3. Basic Algorithms - Classification, Regression, and Clustering 4. Customer Relationship Prediction with Ensembles 5. Affinity Analysis 6. Recommendation Engines with Apache Mahout 7. Fraud and Anomaly Detection 8. Image Recognition with Deeplearning4j 9. Activity Recognition with Mobile Phone Sensors 10. Text Mining with Mallet - Topic Modeling and Spam Detection 11. What Is Next? 12. Other Books You May Enjoy

Other applications in various areas

We looked into affinity analysis to demystify shopping behavior patterns in supermarkets. Although the roots of association rule learning are in analyzing point-of-sale transactions, they can be applied outside the retail industry to find relationships among other types of baskets. The notion of a basket can easily be extended to services and products, for example, to analyze items purchased using a credit card, such as rental cars and hotel rooms, and to analyze information on value-added services purchased by telecom customers (call waiting, call forwarding, DSL, speed call, and so on), which can help the operators determine the ways to improve their bundling of service packages.

Additionally, we will look into the following examples of potential cross industry applications:

  • Medical diagnosis
  • Protein sequences
  • Census data
  • Customer relationship...
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