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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

Hands-on NLP with Spark

In this section, some examples of the implementation of NLP (and its core concepts as described in the previous sections) with Apache Spark are going to be detailed. These examples don't include DL4J or other DL frameworks, as NLP with multilayer neural networks will be the main topic of the next chapter.

While one of the core components of Spark, MLLib, is an ML library, it doesn't provide any facility for NLP. So, you need to use some other NLP library or framework on top of Spark.

Hands-on NLP with Spark and Stanford core NLP

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