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You're reading from  Java Deep Learning Cookbook

Product typeBook
Published inNov 2019
Reading LevelIntermediate
PublisherPackt
ISBN-139781788995207
Edition1st Edition
Languages
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Author (1)
Rahul Raj
Rahul Raj
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Rahul Raj

Rahul Raj has more than 7 years of IT industry experience in software development, business analysis, client communication, and consulting on medium-/large-scale projects in multiple domains. Currently, he works as a lead software engineer in a top software development firm. He has extensive experience in development activities comprising requirement analysis, design, coding, implementation, code review, testing, user training, and enhancements. He has written a number of articles about neural networks in Java and they are featured by DL4J/ official Java community channels. He is also a certified machine learning professional, certified by Vskills, the largest government certification body in India.
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Technical requirements

Make sure the following requirements are satisfied:

  • JDK 8 is installed and added to PATH. Source code requires JDK 8 for execution.
  • Maven is installed/added to PATH. We use Maven to build the application JAR file afterward.

Concrete implementation for the use case discussed in this chapter (Customer retention prediction) can be found at https://github.com/PacktPublishing/Java-Deep-Learning-Cookbook/blob/master/03_Building_Deep_Neural_Networks_for_Binary_classification/sourceCode/cookbookapp/src/main/java/com/javadeeplearningcookbook/examples/CustomerRetentionPredictionExample.java.

After cloning our GitHub repository, navigate to the Java-Deep-Learning-Cookbook/03_Building_Deep_Neural_Networks_for_Binary_classification/sourceCode directory. Then import the cookbookapp project into your IDE as a Maven project by importing pom.xml.

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Java Deep Learning Cookbook
Published in: Nov 2019Publisher: PacktISBN-13: 9781788995207

Author (1)

author image
Rahul Raj

Rahul Raj has more than 7 years of IT industry experience in software development, business analysis, client communication, and consulting on medium-/large-scale projects in multiple domains. Currently, he works as a lead software engineer in a top software development firm. He has extensive experience in development activities comprising requirement analysis, design, coding, implementation, code review, testing, user training, and enhancements. He has written a number of articles about neural networks in Java and they are featured by DL4J/ official Java community channels. He is also a certified machine learning professional, certified by Vskills, the largest government certification body in India.
Read more about Rahul Raj