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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

Interactive Exploratory Data Analysis in Java

Java is a statically typed programming language and code written in Java needs compiling. While Java is good for developing complex data science applications, it makes it harder to interactively explore the data; every time, we need to recompile the source code and re-run the analysis script to see the results. This means that, if we need to read some data, we will have to do it over and over again. If the dataset is large, the program takes more time to start.

So it is hard to interact with data and this makes EDA more difficult in Java than in other languages. In particular, Read-Evaluate-Print Loop (REPL), an interactive shell, is quite an important feature for doing EDA.

Unfortunately, Java 8 does not have REPL, but there are several alternatives:

Other interactive JVM languages such as JavaScript, Groovy, or Scala
Java 9 with jshell
Completely alternative platforms such as Python or R

In this chapter, we will look at the first two options--JVM...

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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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