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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

Table of Contents (17) Chapters

Title Page

Packt Upsell

Contributors

Preface

1. Getting Started with Deep Learning FREE CHAPTER

2. Cancer Types Prediction Using Recurrent Type Networks

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

1. Other Books You May Enjoy

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Index

Frequently asked questions (FAQs)

In this section, we will see some frequently asked questions that might already be on your mind. Answers to these questions can be found in Appendix A.

Can't we train YOLO from scratch?
I was wondering whether we could use the YOLO v3 model.

What changes to the code do I need to make it work for my own video clip?
The application provided can detect cars and another vehicle in the video clip. However, the processing is not smooth. It seems to halt. How can I solve this issue?
Can I extend this app and make it work for a real-time video from a webcam?

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