Java Data Analysis

John R. Hubbard

商品描述

Key Features

  • Get your basics right for data analysis with Java and make sense of your data through effective visualizations.
  • Use various Java APIs and tools such as Rapidminer and WEKA for effective data analysis and machine learning.
  • This is your companion to understanding and implementing a solid data analysis solution using Java

Book Description

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.

What you will learn

  • Develop Java programs that analyze data sets of nearly any size, including text
  • Implement important machine learning algorithms such as regression, classification, and clustering
  • Interface with and apply standard open source Java libraries and APIs to analyze and visualize data
  • Process data from both relational and non-relational databases and from time-series data
  • Employ Java tools to visualize data in various forms
  • Understand multimedia data analysis algorithms and implement them in Java.

About the Author

John R. Hubbard has been doing computer-based data analysis for over 40 years at colleges and universities in Pennsylvania and Virginia. He holds an MSc in computer science from Penn State University and a PhD in mathematics from the University of Michigan. He is currently a professor of mathematics and computer science, Emeritus, at the University of Richmond, where he has been teaching data structures, database systems, numerical analysis, and big data.

Dr. Hubbard has published many books and research papers, including six other books on computing. Some of these books have been translated into German, French, Chinese, and five other languages. He is also an amateur timpanist.

Table of Contents

  1. Introduction to Data Analysis
  2. Data Preprocessing
  3. Data Visualization
  4. Statistics: Elementary statistical methods and their implementation in Java
  5. Relational Database Access
  6. Regression Analysis
  7. Classification Analysis
  8. Cluster Analysis
  9. Recommender Systems
  10. Working with NoSQL Databases
  11. Big Data Analysis with Java
  12. Appendix A

商品描述(中文翻譯)

《主要特點》
- 以Java正確地進行數據分析,並通過有效的可視化方法理解數據。
- 使用Rapidminer和WEKA等各種Java API和工具進行有效的數據分析和機器學習。
- 本書將幫助您理解並實施使用Java的可靠數據分析解決方案。

《書籍描述》
數據分析是一個檢查、清理、轉換和建模數據的過程,旨在發現有用的信息。Java是執行數據分析任務的最受歡迎的語言之一。

本書將幫助您學習Java中的工具和技術,輕鬆進行數據分析。在簡要概述數據科學和相關步驟後,您將學習統計數據分析技術,並使用流行的Java API和庫來實現這些技術。通過實際示例,您還將學習分類和回歸等機器學習概念。

在此過程中,您將熟悉Rapidminer和WEKA等工具,並了解這些基於Java的工具如何有效地進行分析。您還將學習如何分析文本和其他類型的多媒體數據,以及如何處理關聯、非關聯和時間序列數據。本書還將向您展示如何利用不同的基於Java的庫創建深入且易於理解的圖表和圖形。

通過閱讀本書,您將對各種數據分析技術有深入的理解,並學會如何使用Java實現這些技術。

《學到什麼》
- 開發Java程序,分析幾乎任何大小的數據集,包括文本數據
- 實現重要的機器學習算法,如回歸、分類和聚類
- 使用標準的開源Java庫和API進行數據分析和可視化
- 處理關聯和非關聯數據庫以及時間序列數據
- 使用Java工具以各種形式可視化數據
- 理解多媒體數據分析算法並在Java中實現

《作者簡介》
約翰·R·哈伯德(John R. Hubbard)在賓夕法尼亞州和維吉尼亞州的大學和學院從事基於計算機的數據分析工作已有40多年。他擁有賓夕法尼亞州立大學的計算機科學碩士學位和密歇根大學的數學博士學位。他目前是里士滿大學(University of Richmond)的數學和計算機科學教授,並擔任名譽教授。他在該校教授數據結構、數據庫系統、數值分析和大數據等課程。

哈伯德博士出版了許多書籍和研究論文,其中包括其他六本關於計算機的書籍。其中一些書籍已經被翻譯成德語、法語、中文和其他五種語言。他還是一位業餘定音鼓手。

《目錄》
1. 數據分析入門
2. 數據預處理
3. 數據可視化
4. 統計:Java中的基本統計方法及其實現
5. 關聯數據庫訪問
6. 回歸分析
7. 分類分析
8. 聚類分析
9. 推薦系統
10. 使用非關聯數據庫
11. 使用Java進行大數據分析
12. 附錄A