Numeric Computation and Statistical Data Analysis on the Java Platform

Viac o knihe

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 programming languages, including Java, Groovy, Ruby, and BeanShell. The author provides a versatile computational platform that transcends the limitations of single-language statistical programs. Covering a wide range of topics, the book begins with an introduction to Python on the Java platform (Jython) and progresses to descriptive statistics, symbolic calculations, neural networks, non-linear regression analysis, and various data-mining techniques. It guides readers on identifying patterns in real-world data, classifying data, and processing it for knowledge discovery. The concise code snippets are designed to fit on single pages for ease of use. This resource is ideal for those interested in learning how to perform statistical data analysis using popular programming languages, integrating data analysis algorithms into full-scale applications, and deploying calculations on web pages or computational servers across different operating systems. It serves as an excellent reference for scientific computations aimed at solving real-world problems, supported by a comprehensive stack of open-source Java libraries from the DataMelt (DMelt) project, appealing to data-analysis scientists, engineers, and students a