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Hands-On Deep Learning with Apache Spark

You're reading from   Hands-On Deep Learning with Apache Spark Build and deploy distributed deep learning applications on Apache Spark

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Product type Paperback
Published in Jan 2019
Publisher Packt
ISBN-13 9781788994613
Length 322 pages
Edition 1st Edition
Languages
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Author (1):
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Guglielmo Iozzia Guglielmo Iozzia
Author Profile Icon Guglielmo Iozzia
Guglielmo Iozzia
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Table of Contents (19) Chapters Close

Preface 1. The Apache Spark Ecosystem FREE CHAPTER 2. Deep Learning Basics 3. Extract, Transform, Load 4. Streaming 5. Convolutional Neural Networks 6. Recurrent Neural Networks 7. Training Neural Networks with Spark 8. Monitoring and Debugging Neural Network Training 9. Interpreting Neural Network Output 10. Deploying on a Distributed System 11. NLP Basics 12. Textual Analysis and Deep Learning 13. Convolution 14. Image Classification 15. What's Next for Deep Learning? 16. Other Books You May Enjoy Appendix A: Functional Programming in Scala 1. Appendix B: Image Data Preparation for Spark

What's Next for Deep Learning?

This final chapter will try to give an overview of what's in store for the future of deep learning (DL) and, more generally, for AI.

We will be covering the following topics in this chapter:

  • DL and AI
  • Hot topics
  • Spark and Reinforcement Learning (RL)
  • Support for Generative Adversarial Networks (GANs) in DL4J

The rapid advancement of technology not only speeds up the implementation of existing AI ideas, it creates new opportunities in this space that would have been unthinkable one or two years ago. Day by day, AI is finding new practical applications in diverse areas and is radically transforming the way we do business in them. Therefore, it would be impossible to cover all of the new scenarios, so we are going to focus on some particular contexts/areas where we have been directly or indirectly involved.

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