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Java Deep Learning Projects

You're reading from Java Deep Learning Projects

Product type Book

Published in Jun 2018

Publisher Packt

ISBN-13 9781788997454

Pages 436 pages

Edition 1st Edition

Languages

Concepts

Table of Contents (13) Chapters

Preface

1. Getting Started with Deep Learning

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

12. Other Books You May Enjoy

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Frequently asked questions (FAQs)

Now that we have solved the video classification problem, but with low accuracy, there are other practical aspects of this problem and overall deep learning phenomena that need to be considered too. In this section, we will see some frequently asked questions that may be on your mind. Answers to these questions can be found in Appendix A.

My machine has multiple GPUs installed (for example, two), but DL4J is using only one. How do I fix this problem?
I have configured a p2.8 xlarge EC2 GPU compute instance on AWS. However, it is showing low disk space while installing and configuring CUDA and cuDNN. How to fix this issue?
I understand how the distributed training happens on AWS EC2 AMI instance. However, my machine has a low-end GPU, and often I get OOP on the GPU. How can solve the issue?
Can I treat this application as a human activity recognition...

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