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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):

Richard M. Reese

Jennifer L. Reese

View More author details

Table of Contents (19) Chapters

Java for Data Science

Credits

About the Authors

About the Reviewers

www.PacktPub.com

Customer Feedback

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

Chapter 3. Data Cleaning

Real-world data is frequently dirty and unstructured, and must be reworked before it is usable. Data may contain errors, have duplicate entries, exist in the wrong format, or be inconsistent. The process of addressing these types of issues is called data cleaning. Data cleaning is also referred to as data wrangling, massaging, reshaping , or munging. Data merging, where data from multiple sources is combined, is often considered to be a data cleaning activity.

We need to clean data because any analysis based on inaccurate data can produce misleading results. We want to ensure that the data we work with is quality data. Data quality involves:

Validity: Ensuring that the data possesses the correct form or structure
Accuracy: The values within the data are truly representative of the dataset
Completeness: There are no missing elements
Consistency: Changes to data are in sync
Uniformity: The same units of measurement are used

There are several techniques and tools used...

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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.

See other products by Reese

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