computation, knowledge discovery and statistical data analysis integrated with
powerful 2D and 3D graphics for visualization are the key topics of this book. The
Python code examples powered by the Java platform can easily be transformed to
other programming languages, such as Java, Groovy, Ruby and BeanShell. This
book equips the reader with a
computational platform which, unlike other statistical programs, is not limited
by a single programming language.
The author
focuses on practical programming aspects and covers a broad range of topics,
from basic introduction to the Python language on the Java platform (Jython),
to descriptive statistics, symbolic calculations, neural networks, non-linear
regression analysis and many other data-mining topics. He discusses how to find
regularities in real-world data, how to classify data, and how to process data
for knowledge discoveries. The code snippets are so short that they easily fit into
single pages.
Numeric Computation and Statistical Data
Analysis on the Java Platform is a great choice for those who want to learn how statistical
data analysis can be done using popular programming languages, who want to
integrate data analysis algorithms in full-scale applications, and deploy such
calculations on the web pages or computational servers regardless
of their operating system. It is an excellent reference for scientific computations to solve
real-world problems using a comprehensive stack of open-source Java
libraries included in the DataMelt (DMelt) project and will be
appreciated by many data-analysis scientists, engineers and students.
