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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

Functional programming (FP)

In FP, functions are first-class citizens—this means that they are treated like any other values and can be passed as arguments to other functions or be returned as a result of a function. In FP, it is also possible to work with functions in the so-called literal form, with no need to name them. Let's look at the following Scala example:

val integerSeq = Seq(7, 8, 9, 10)
integerSeq.filter(i => i % 2 == 0)

i => i % 2 == 0 is a function literal without a name. It checks whether a number is even. It can be passed as another function argument or it can be used as a return value.

Purity

One of the pillars of functional programming is pure functions. A pure programming function is a function...

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