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Java for Data Science

You're reading from Java for Data Science Examine the techniques and Java tools supporting the growing field of data science

Product type Paperback

Published in Jan 2017

Publisher Packt

ISBN-13 9781785280115

Length 386 pages

Edition 1st Edition

Languages

Java

Tools

Deeplearning4j

Concepts

Data Science

Authors (2):

Jennifer L. Reese

Richard M. Reese

View More author details

Table of Contents (13) Chapters

Preface

1. Getting Started with Data Science FREE CHAPTER

2. Data Acquisition

3. Data Cleaning

4. Data Visualization

5. Statistical Data Analysis Techniques

6. Machine Learning

7. Neural Networks

8. Deep Learning

9. Text Analysis

10. Visual and Audio Analysis

11. Mathematical and Parallel Techniques for Data Analysis

12. Bringing It All Together

Regression analysis

Regression analysis is useful for determining trends in data. It indicates the relationship between dependent and independent variables. The independent variables determine the value of a dependent variable. Each independent variable can have either a strong or a weak effect on the value of the dependent variable. Linear regression uses a line in a scatterplot to show the trend. Non-linear regression uses some sort of curve to depict the relationships.

For example, there is a relationship between blood pressure and various factors such as age, salt intake, and Body Mass Index (BMI). The blood pressure can be treated as the dependent variable and the other factors as independent variables. Given a dataset containing these factors for a group of individuals we can perform regression analysis to see trends.

There are several types of regression analysis supported by Java. We will be examining simple linear regression and multiple linear regression. Both approaches take a...

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Authors (2)

Richard M. Reese

Richard M. Reese

Richard Reese has worked in the industry and academics for the past 29 years. For 10 years he provided software development support at Lockheed and at one point developed a C based network application. He was a contract instructor providing software training to industry for 5 years. Richard is currently an Associate Professor at Tarleton State University in Stephenville Texas. Richard is the author of various books and video courses some of which are as follows: Natural Language Processing with Java. Java for Data Science Getting Started with Natural Language Processing in Java

See other products by Richard M. Reese

Reese

Reese

Jennifer L. Reese studied computer science at Tarleton State University. She also earned her M.Ed. from Tarleton in December 2016. She currently teaches computer science to high-school students. Her interests include the integration of computer science concepts with other academic disciplines, increasing diversity in computer science courses, and the application of data science to the field of education. She has co-authored two books: Java for Data Science and Java 7 New Features Cookbook. She previously worked as a software engineer. In her free time she enjoys reading, cooking, and traveling—especially to any destination with a beach. She is a musician and appreciates a variety of musical genres.

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