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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 Recognition with Deeplearning4j

Images have become ubiquitous in web services, social networks, and web stores. In contrast to humans, computers have great difficulty in understanding what is in the image and what it represents. In this chapter, we'll first look at the challenges behind teaching computers how to understand images, and then focus on an approach based on deep learning. We'll look at a high-level theory thats required to configure a deep learning model and discuss how to implement a model that is able to classify images using a Java library, Deeplearning4j.

This chapter will cover the following topics:

  • Introducing image recognition
  • Discussing deep learning fundamentals
  • Building an image recognition model
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