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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

Frequently asked questions (FAQs)

Now that we have solved the sentiment analysis problem with an acceptable level of 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 might already be on your mind. Answers to these questions can be found in Appendix A:

  1. I understand that the predictive accuracy of sentiment analysis using LSTM is still reasonable. However, it does not perform well on the Sentiment labeled dataset. Did our network overfit? Is there any way to observe how the training went?
  2. Considering a huge number of review texts, can we perform the training on the GPU?
  3. In relation to question 2, can we even undertake the whole process using Spark?
  4. Where can I get more training datasets for sentiment analysis?
  5. Instead of downloading the...
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