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Mastering Java for Data Science

You're reading from Mastering Java for Data Science

Product type Book

Published in Apr 2017

Publisher Packt

ISBN-13 9781782174271

Pages 364 pages

Edition 1st Edition

Languages

Concepts

Machine Learning

Author (1):

Alexey Grigorev

Table of Contents (17) Chapters

Title Page

Credits

About the Author

About the Reviewers

www.PacktPub.com

Customer Feedback

Preface

1. Data Science Using Java

2. Data Processing Toolbox

3. Exploratory Data Analysis

4. Supervised Learning - Classification and Regression

5. Unsupervised Learning - Clustering and Dimensionality Reduction

6. Working with Text - Natural Language Processing and Information Retrieval

7. Extreme Gradient Boosting

8. Deep Learning with DeepLearning4J

9. Scaling Data Science

10. Deploying Data Science Models

Apache Spark

Apache Spark is a framework for scalable data processing. It was designed to be better than Hadoop: it tries to process data in memory and not to save intermediate results on disk. Additionally, it has more operations, not just map and reduce, and thus richer APIs.

The main unit of abstraction in Apache Spark is Resilient Distributed Dataset (RDD), which is a distributed collection of elements. The key difference from usual collections or streams is that RDDs can be processed in parallel across multiple machines, in the same way, Hadoop jobs are processed.

There are two types of operations we can apply to RDDs: transformations and actions.

Transformations: As the name suggests, it only changes data from one form to another. As input, they receive an RDD, and they also output an RDD. Operations such as map, flatMap, or filter are examples of transformation operations.
Actions: These take in an RDD and produce something else, for example, a value, a list, or a map, or save the results...

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Authors (1)

Alexey Grigorev

Alexey Grigorev is a skilled data scientist, machine learning engineer, and software developer with more than 8 years of professional experience. He started his career as a Java developer working at a number of large and small companies, but after a while he switched to data science. Right now, Alexey works as a data scientist at Simplaex, where, in his day-to-day job, he actively uses Java and Python for data cleaning, data analysis, and modeling. His areas of expertise are machine learning and text mining.

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