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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

Data ingestion from S3

Nowadays, there's a big chance that the training and test data are hosted in some cloud storage system. In this section, we are going to learn how to ingest data through Apache Spark from an object storage such as Amazon S3 (https://aws.amazon.com/s3/) or S3-based (such as Minio, https://www.minio.io/). The Amazon simple storage service (which is more popularly known as Amazon S3) is an object storage service part of the AWS cloud offering. While S3 is available in the public cloud, Minio is a high performance distributed object storage server compatible with the S3 protocol and standards that has been designed for large-scale private cloud infrastructures.

We need to add to the Scala project the Spark core and Spark SQL dependencies, and also the following:

groupId: com.amazonaws
artifactId: aws-java-sdk-core
version1.11.234

groupId: com.amazonaws...
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