Java Data Analysis : Data Mining, Big Data Analysis, NoSQL, and Data Visualization
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| Titel: | Java Data Analysis : Data Mining, Big Data Analysis, NoSQL, and Data Visualization |
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| Beschreibung: | Get the most out of the popular Java libraries and tools to perform efficient data analysisKey FeaturesGet 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 JavaBook DescriptionData 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 learnDevelop Java programs that analyze data sets of nearly any size, including textImplement important machine learning algorithms such as regression, classification, and clusteringInterface with and apply standard open source Java libraries and APIs to analyze and visualize dataProcess data from both relational and non-relational databases and from time-series dataEmploy Java tools to visualize data in various formsUnderstand multimedia data analysis algorithms and implement them in Java.Who 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. |
| Autoren: | John R. Hubbard |
| Resource Type: | eBook. |
| Schlagworte: | Relational databases, Relational databases--Computer programs, Java (Computer program language)--Handbooks, manuals, etc, Java (Computer program language), Regression analysis--Computer programs, Electronic data processing, Information visualization, Data mining |
| Categories: | COMPUTERS / Data Science / General, COMPUTERS / Data Science / Data Modeling & Design, COMPUTERS / Data Science / Data Visualization |
| Datenbank: | eBook Index |
| Abstract: | Get the most out of the popular Java libraries and tools to perform efficient data analysisKey FeaturesGet 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 JavaBook DescriptionData 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 learnDevelop Java programs that analyze data sets of nearly any size, including textImplement important machine learning algorithms such as regression, classification, and clusteringInterface with and apply standard open source Java libraries and APIs to analyze and visualize dataProcess data from both relational and non-relational databases and from time-series dataEmploy Java tools to visualize data in various formsUnderstand multimedia data analysis algorithms and implement them in Java.Who 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. |
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| ISBN: | 9781787285651 9781787286405 |