Book Image

Java Data Analysis

By : John R. Hubbard
Book Image

Java Data Analysis

By: John R. Hubbard

Overview of this book

Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the aim of discovering useful information. Java is one of the most popular languages to perform your data analysis tasks. This book will help you learn the tools and techniques in Java to conduct data analysis without any hassle. After getting a quick overview of what data science is and the steps involved in the process, you’ll learn the statistical data analysis techniques and implement them using the popular Java APIs and libraries. Through practical examples, you will also learn the machine learning concepts such as classification and regression. In the process, you’ll familiarize yourself with tools such as Rapidminer and WEKA and see how these Java-based tools can be used effectively for analysis. You will also learn how to analyze text and other types of multimedia. Learn to work with relational, NoSQL, and time-series data. This book will also show you how you can utilize different Java-based libraries to create insightful and easy to understand plots and graphs. By the end of this book, you will have a solid understanding of the various data analysis techniques, and how to implement them using Java.
Table of Contents (20 chapters)
Java Data Analysis
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
Index

Actuarial science


One of Newton's few friends was Edmund Halley, the man who first computed the orbit of his eponymous comet. Halley was a polymath, with expertise in astronomy, mathematics, physics, meteorology, geophysics, and cartography.

In 1693, Halley analyzed mortality data that had been compiled by Caspar Neumann in Breslau, Germany. Like Kepler's work with Brahe's data 90 years earlier, Halley's analysis led to new knowledge. His published results allowed the British government to sell life annuities at the appropriate price, based on the age of the annuitant.

Most data today is still numeric. But most of the algorithms we will be studying apply to a much broader range of possible values, including text, images, audio and video files, and even complete web pages on the internet.