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You're reading from Hands-On Deep Learning with Apache Spark Build and deploy distributed deep learning applications on Apache Spark

Product type Paperback

Published in Jan 2019

Publisher Packt

ISBN-13 9781788994613

Length 322 pages

Edition 1st Edition

Languages

Java

Tools

Apache Spark

Concepts

Deep Learning

Author (1):

Guglielmo Iozzia

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Table of Contents (19) Chapters

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

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Appendix A: Functional Programming in Scala

Functional programming (FP)

1. Appendix B: Image Data Preparation for Spark

Image preprocessing

Appendix B: Image Data Preparation for Spark

CNNs are among the main topics of this book. They are used in lots of practical applications of image classification and analysis. This Appendix explains how to create a RDD<DataSet> to train a CNN model for image classification.

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Authors (1)

Iozzia

Guglielmo Iozzia is currently a big data delivery manager at Optum in Dublin. He completed his master's degree in biomedical engineering at the University of Bologna. After graduation, he joined a start-up IT company in Bologna that had implemented a new system to manage online payments. There, he worked on complex Java projects for different customers in different areas. He has also worked at the IT department of FAO, an agency of the United Nations. In 2013, he had the chance to join IBM in Dublin. There, he improved his DevOps skills, working mostly on cloud-based applications. He is a golden member, writes articles at DZone, and maintains a personal blog to share his findings and thoughts about various tech topics.

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