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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

Standard Java library

The standard Java library is very rich and offers a lot of tools for data manipulation, including:

Collections for organizing data in memory
I/O for reading and writing data
Streaming APIs for making data transformations easy

In this chapter, we will look at all these tools in detail.

Collections

Data is the most important part of data science. When dealing with data, it needs to be efficiently stored and processed, and for this we use data structures. A data structure describes a way to store data efficiently to solve a specific problem, and the Java Collection API is the standard Java API for data structures. This API offers a wide variety of implementations that are useful in practical data science applications.

We will not describe the collection API in full detail, but concentrate on the most useful and important ones--list, set, and map interfaces.

Lists are collections where each element can be accessed by its index. The g0-to implementation of the List interface is...

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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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