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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

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Product type Paperback
Published in Jun 2018
Publisher Packt
ISBN-13 9781788997454
Length 436 pages
Edition 1st Edition
Languages
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Author (1):
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Md. Rezaul Karim Md. Rezaul Karim
Author Profile Icon Md. Rezaul Karim
Md. Rezaul Karim
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Toc

Table of Contents (13) Chapters Close

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

Answers to questions

Answer to question 1: This means the training is not being distributed, which also means that your system is forcing you to use just one GPU. Now to solve this issue, just add the following line at the beginning of your main() method:

CudaEnvironment.getInstance().getConfiguration().allowMultiGPU(true);

Answer to question 2: Well, this is certainly an AWS EC2-related question. However, I will provide a short explanation. If you see the default boot device, it allocates only 7.7 GB of space, but about 85% is allocated for the udev device, as shown here:

Showing storage on a p2.8xlarge instance

Now, to get rid of this issue, you can specify sufficient storage in the boot device while creating the instance, as follows:

Increasing storage on the default boot device the on p2.8xlarge instance

Answer to question 3: Well, if this is the case, you can probably do...

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