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020 _a9783319285313
040 _aES-MaUEC
050 4 _aQA76.9.I52
_bC445 2016
082 0 4 _a005.13
100 1 _aChekanov, Sergei V.
_998438
_0Local
245 1 0 _aNumeric Computation and Statistical Data Analysis on the Java Platform
_cby Sergei V Chekanov
260 _aCham
_bSpringer International Publishing
_c2016
300 _a1 recurso en línea (XXVI, 620 páginas)
_b92 ilustraciones
336 _aTexto
_btxt
_2rdacontent
337 _aelectrónico
_bc
_2rdamedia
338 _arecurso electrónico
_bcr
_2rdacarrier
490 0 _aAdvanced Information and Knowledge Processing
_x1610-3947
505 0 _aJava Computational Platform -- Introduction to Jython -- Mathematical Functions -- Data Arrays -- Linear Algebra and Equations -- Symbolic Computations -- Histograms -- Scientific Visualization -- File Input and Output -- Probability and Statistics -- Linear Regression and Curve Fitting -- Data Analysis and Data Mining -- Neural Networks -- Finding Regularities and Data Classification -- Miscellaneous Topics -- Using Other Languages on the Java Platform -- Octave-style Scripting Using Java -- Index -- Index of Code Examples.
520 3 _aNumerical 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.
710 2 _aSpringerLink (Online service)
_0Local
_9106996
942 _2lcc
_cLE
988 _aEBOOK, asignarmaterias , EBSPRINGER
650 0 7 _aLenguajes de programación
_0
_2embne
_9678605
650 7 _aPython (Lenguaje de programación)
_0(OCoLC)1084736
_2embne
_0
_9161036
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-3-319-28531-3
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
901 _ai9783319285313
907 _a.b12947428
_b10-10-17
_c21-11-16
998 _am
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