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Hands-On Deep Learning with Apache Spark

You're reading from  Hands-On Deep Learning with Apache Spark

Product type Book
Published in Jan 2019
Publisher Packt
ISBN-13 9781788994613
Pages 322 pages
Edition 1st Edition
Languages
Author (1):
Guglielmo Iozzia Guglielmo Iozzia
Profile icon Guglielmo Iozzia
Toc

Table of Contents (19) Chapters close

Preface 1. The Apache Spark Ecosystem 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 first went deeper into the RNNs' main concepts, before understanding how many practical use cases these particular NNs have, and, finally, we started going hands-on, implementing some RNNs using DL4J and Spark.

The next chapter will focus on training techniques for CNN and RNN models. Training techniques have just been mentioned, or skipped from Chapter 3, Extract, Transform, Load, to this chapter because the main goal so far has been on understanding how training data can be retrieved and prepared and how models can be implemented through DL4J and Spark.

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