Numeric Computation and Statistical Data Analysis on the Java Platform

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This book focuses on numerical computation, knowledge discovery, and statistical data analysis, enhanced by powerful 2D and 3D graphics for visualization. It features Python code examples that can be easily adapted to other languages like Java, Groovy, Ruby, and BeanShell, providing a versatile computational platform not restricted to a single programming language. The author emphasizes practical programming, covering a wide range of topics from an introduction to Python on the Java platform (Jython) to descriptive statistics, symbolic calculations, neural networks, non-linear regression, and various data-mining techniques. Key discussions include identifying patterns in real-world data, classifying data, and processing it for knowledge discovery. The code snippets are concise, fitting comfortably on single pages. This resource is ideal for those interested in statistical data analysis using popular programming languages, integrating data analysis algorithms into applications, and deploying calculations on web pages or computational servers across different operating systems. It serves as a valuable reference for scientific computations aimed at solving real-world problems, utilizing a comprehensive array of open-source Java libraries from the DataMelt (DMelt) project, appealing to data-analysis scientists, engineers, and students alike.