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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

Image classification

In this section, we will discuss how to implement some of the neural network structures with the Deeplearning4j library. Let's get started.

Deeplearning4j

As we discussed in Chapter 2, Java Libraries and Platforms for Machine Learning, Deeplearning4j is an open source, distributed deep learning project in Java and Scala. Deeplearning4j relies on Spark and Hadoop for MapReduce, trains models in parallel, and iteratively averages the parameters they produce in a central model. A detailed library summary is presented in Chapter 2, Java Libraries and Platforms for Machine Learning.

Getting DL4J

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