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Mastering Apache Spark 2.x - Second Edition

You're reading from Mastering Apache Spark 2.x - Second Edition

Product type Book

Published in Jul 2017

Publisher Packt

ISBN-13 9781786462749

Pages 354 pages

Edition 2nd Edition

Languages

Concepts

Table of Contents (21) Chapters

Title Page

Credits

About the Author

About the Reviewer

www.PacktPub.com

Customer Feedback

Preface

1. A First Taste and What’s New in Apache Spark V2

2. Apache Spark SQL

3. The Catalyst Optimizer

4. Project Tungsten

5. Apache Spark Streaming

6. Structured Streaming

7. Apache Spark MLlib

8. Apache SparkML

9. Apache SystemML

10. Deep Learning on Apache Spark with DeepLearning4j and H2O

11. Apache Spark GraphX

12. Apache Spark GraphFrames

13. Apache Spark with Jupyter Notebooks on IBM DataScience Experience

14. Apache Spark on Kubernetes

What does the new API look like?

When it comes to machine learning on Apache Spark, we are used to transforming data into an appropriate format and data types before we actually feed them to our algorithms. Machine learning practitioners around the globe discovered that the preprocessing tasks on a machine learning project usually follow the same pattern:

Data preparation
Training
Evaluating
Hyperparameter tuning

Therefore, the new ApacheSparkML API supports this process out of the box. It is called pipelines and is inspired by scikit-learn http://scikit-learn.org, a very popular machine learning library for the Python programming language. The central data structure is a DataFrame and all operations run on top of it.

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