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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

Chapter 3. Exploratory Data Analysis

In the previous chapter, we covered data processing, which is an important step for transforming data into a form usable for analysis. In this chapter, we take the next logical step after cleaning and look at data. This step is called Exploratory Data Analysis (EDA), and it consists of summarizing data and creating visualizations.

In this chapter, we will cover the following topics:

Summary statistics with Apache Commons Math and Joinery
Interactive shells for EDA in Java and JVM

By the end of this chapter, you will know how to calculate summary statistics and create simple graphs with Joinery.

The rest of the chapter is locked

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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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