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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

Convolutional Neural Networks

In Chapter 2, Deep Learning Basics, we learned about a very high level overview of Convolutional Neural Networks (CNNs). In this chapter, we are going to understand more details about this type of CNN, the possible implementations of their layers, and we will start hands-on implementing CNNs through the DeepLearning4j framework. The chapter ends with examples involving Apache Spark too. Training and evaluation strategies for CNNs will be covered in Chapter 7, Training Neural Networks with Spark, Chapter 8, Monitoring and Debugging Neural Network Training, and Chapter 9, Interpreting Neural Network Output. In the description of the different layers, I have tried to reduce the usage of math concepts and formulas as much as possible in order to make the reading and comprehension easier for developers and data analysts who might have no math or data science...

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