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Java Data Analysis

You're reading from   Java Data Analysis Data mining, big data analysis, NoSQL, and data visualization

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Product type Paperback
Published in Sep 2017
Publisher Packt
ISBN-13 9781787285651
Length 412 pages
Edition 1st Edition
Languages
Concepts
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Author (1):
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John R. Hubbard John R. Hubbard
Author Profile Icon John R. Hubbard
John R. Hubbard
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Table of Contents (14) Chapters Close

Preface 1. Introduction to Data Analysis 2. Data Preprocessing FREE CHAPTER 3. Data Visualization 4. Statistics 5. Relational Databases 6. Regression Analysis 7. Classification Analysis 8. Cluster Analysis 9. Recommender Systems 10. NoSQL Databases 11. Big Data Analysis with Java A. Java Tools Index

Why Java?

Java is, as it has been for over a decade, the most popular programming language in the world. And its popularity is growing. There are several good reasons for this:

  • Java runs the same way on all computers
  • It supports the object-oriented programming (OOP) paradigm
  • It interfaces easily with other languages, including the database query language SQL
  • Its Javadoc documentation is easy to access and use
  • Most open-source software is written in Java, including that which is used for data analysis

Python may be easier to learn, R may be simpler to run, JavaScript may be easier for developing websites, and C/C++ may be faster, but for general purpose programming, Java can't be beat.

Java was developed in 1995 by a team led by James Gosling at Sun Microsystems. In 2010, the Oracle Corporation bought Sun for $7.4 B and has supported Java since then. The current version is Java 8, released in 2014. But by the time you buy this book, Java 9 should be available; it is scheduled to be released in late 2017.

As the title of this book suggests, we will be using Java in all our examples.

Note

Appendix includes instructions on how to set up your computer with Java.

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