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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 solved the dog versus cat classification problem with outstanding accuracy, there are other practical aspects of transfer learning and overall deep learning phenomena that need to be considered too. 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 I train the model with my own animal images?
Training using all the images is taking too long. What can I do?
Can I wrap up this application as a web app?
Can I use VGG-19 for this task?
How many hyperparameters do we have? I also want to see for each layer.

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