Numerical 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*.*
