Java Data Analysis
Idioma: inglés
Editorial: Packt Publishing Limited, GB, 2017
- Tapa blanda
- Nuevo

Librería: Rarewaves.com USA, London, London, Reino UnidoRarewaves.com USA
Vendedor de AbeBooks desde 11 de junio de 2025
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EUR 69,56
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Get the most out of the popular Java libraries and tools to perform efficient data analysisAbout This Book. 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 JavaWho This Book Is ForIf you are a student or Java developer or a budding data scientist who wishes to learn the fundamentals of data analysis and learn to perform data analysis with Java, this book is for you. Some familiarity with elementary statistics and relational databases will be helpful but is not mandatory, to get the most out of this book. A firm understanding of Java is required.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.In DetailData 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.Style and approachThe book takes a very comprehensive approach to enhance your understanding of data analysis. Sufficient real-world examples and use cases are included to help you grasp the concepts quickly and apply them easily in your day-to-day work. Packed with clear, easy-to-follow examples, this book will turn you into an ace data analyst in no time. …
N° de ref. del artículo LU-9781787285651
- Título
- Java Data Analysis
- Autor
- John R. Hubbard
- Editorial
- Packt Publishing Limited, GB
- Año de publicación
- 2017
- Estado
- New
- Encuadernación
- Paperback
- Idioma
- inglés
- ISBN 10
- 1787285650
- ISBN 13
- 9781787285651
- Dimensiones
- 23.5 x 19.1 x 2.18 cm
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
- Introduction to Data Analysis
- Data Preprocessing
- Data Visualization
- Statistics: Elementary statistical methods and their implementation in Java
- Relational Database Access
- Regression Analysis
- Classification Analysis
- Cluster Analysis
- Recommender Systems
- Working with NoSQL Databases
- Big Data Analysis with Java
- Appendix A
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Rarewaves.com USA
London, London, Reino Unido
Vendedor de AbeBooks desde 11 de junio de 2025
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