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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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Frequently asked questions (FAQs)

Now that we have seen how to develop a movie recommendation that predicts both the rating and ranking of movies by users, there are some issues that require our attention, too. Also, we couldn't cover/discuss the library in this chapter, so I suggest that you read the documentation more carefully.

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

How can I save a trained FM model?
How can I restore a saved FM model from disk?
Can I use the FM algorithm for solving a classification task?
Give me a few example use cases where FM algorithms have been used.
Can I use the FM algorithm for making top-N recommendations?

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