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Java Deep Learning Projects

You're reading from Java Deep Learning Projects Implement 10 real-world deep learning applications using Deeplearning4j and open source APIs

Product type Paperback

Published in Jun 2018

Publisher Packt

ISBN-13 9781788997454

Length 436 pages

Edition 1st Edition

Languages

Java

Tools

Deeplearning4j

Concepts

Deep Learning

Author (1):

Md. Rezaul Karim

View More author details

Table of Contents (13) Chapters

Preface

1. Getting Started with Deep Learning

2. Cancer Types Prediction Using Recurrent Type Networks FREE CHAPTER

3. Multi-Label Image Classification Using Convolutional Neural Networks

4. Sentiment Analysis Using Word2Vec and LSTM Network

5. Transfer Learning for Image Classification

6. Real-Time Object Detection using YOLO, JavaCV, and DL4J

7. Stock Price Prediction Using LSTM Network

8. Distributed Deep Learning – Video Classification Using Convolutional LSTM Networks

9. Playing GridWorld Game Using Deep Reinforcement Learning

10. Developing Movie Recommendation Systems Using Factorization Machines

11. Discussion, Current Trends, and Outlook

12. Other Books You May Enjoy

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Developing an image classifier using transfer learning

In the next section, we will see how to distinguish between dogs and cats based on their raw images. We will also see how to implement our first CNN model to deal with the raw and color image having three channels.

This project is highly inspired (but extended significantly) by the "Java Image Cat&Dog Recognition with Deep Neural Networks" article by Klevis Ramo (http://ramok.tech/).

The code folder has three packages with a few Java files in each. Their functionalities are outlined as follows:

com.packt.JavaDL.DogvCatClassification.Train:
- TrainCatvsDogVG16.java: It is used to train the network and the trained model is saved to a user specific location. Finally, it prints the results.
- PetType.java: Contains an enum type that specifies pet types (that is, cat, dog, and unknown).
- VG16CatvDogEvaluator.java: Restores...

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