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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

Summary

In this chapter, we concluded this book by discussing some aspects of model deployment, and we looked into standards for the data science process and the interchangeable predictive model format. We also reviewed online courses, competitions, web resources, and conferences that could help you in your journey towards mastering the art of machine learning.

I hope this book inspired you to dive deeper into data science and has motivated you to get your hands dirty, experiment with various libraries, and get a grasp of how different problems could be attacked. Remember, all of the source code and additional resources are available on the Packt Publishing website: https://www.packtpub.com/.

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