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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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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: Yes, of course, you can. However, please note that you have to provide a sufficient number of images, preferably at least a few thousand images for each animal type. Otherwise, the model will not be trained well.

Answer to question 2: A possible reason could be you are trying to feed all the images at once or you are training on CPU (and your machine does not have a good configuration). The former can be addressed easily; we can undertake the training in batch mode, which is recommended for the era of deep learning.

The latter case can be addressed by migrating your training from CPU to GPU. However, if your machine does not have a GPU, you can try migrating to Amazon GPU instance to get the support for a single (p2.xlarge) or multiple GPUs (for example, p2.8xlarge).

Answer to question 3: The application provided should be enough to understand...

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