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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

Summary

In this chapter, we became familiar with Apache Spark and most of its main modules. We started to use the available Spark shells and wrote our first self-contained application using the Scala and Python programming languages. Finally, we explored different ways of deploying and running Spark in cluster mode. Everything we have learned about so far is necessary for understanding the topics that are presented from Chapter 3, Extract, Transform, Load, onward. If you have any doubts about any of the presented topics, I suggest that you go back and read this chapter again before moving on.

In the next chapter, we are going to explore the basics of DL, with an emphasis on some particular implementations of multi-layer neural networks.

You have been reading a chapter from
Hands-On Deep Learning with Apache Spark
Published in: Jan 2019
Publisher: Packt
ISBN-13: 9781788994613
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