Python For Scientific Computing

Pandas Cookbook: Recipes for Scientific Computing, Time Series Analysis and Data Visualization using Python

Pandas Cookbook: Recipes for Scientific Computing, Time Series Analysis and Data Visualization using Python by Theodore Petrou
English | 23 Oct. 2017 | ISBN: 1784393878 | ASIN: B06W2LXLQK | 538 Pages | AZW3 | 21.43 MB

New Challenges in Grid Generation and Adaptivity for Scientific Computing  eBooks & eLearning

Posted by ChrisRedfield at Nov. 22, 2017
New Challenges in Grid Generation and Adaptivity for Scientific Computing

Simona Perotto, Luca Formaggia - New Challenges in Grid Generation and Adaptivity for Scientific Computing
Published: 2015-04-28 | ISBN: 331906052X, 3319359266 | PDF | 325 pages | 12.68 MB

Scientific Computing with Python 3  eBooks & eLearning

Posted by AlenMiler at Dec. 29, 2016
Scientific Computing with Python 3

Scientific Computing with Python 3 by Claus Fuhrer
English | 23 Dec. 2016 | ISBN: 1786463512 | 332 Pages | AZW3/MOBI/EPUB/PDF (conv) | 17.95 MB
Parallel Processing for Scientific Computing (Software, Environments and Tools) (repost)

Parallel Processing for Scientific Computing (Software, Environments and Tools) by Michael A. Heroux, Padma Raghavan and Horst D. Simon
English | November 1, 2006 | ISBN-10: 0898716195 | 397 pages | DJVU | 4.7 Mb

Modern Software Tools for Scientific Computing by A. Bruaset  eBooks & eLearning

Posted by tanas.olesya at July 12, 2015
Modern Software Tools for Scientific Computing by A. Bruaset

Modern Software Tools for Scientific Computing by A. Bruaset
English | Apr 1, 1997 | ISBN: 1461273684 | 385 Pages | PDF | 23 MB

Looking back at the years that have passed since the realization of the very first electronic, multi-purpose computers, one observes a tremendous growth in hardware and software performance.
"MATLAB: A Fundamental Tool for Scientific Computing and Engineering Applications, Volume 3" ed. by Vasilios N. Katsikis

"MATLAB: A Fundamental Tool for Scientific Computing and Engineering Applications, Volume 3" ed. by Vasilios N. Katsikis
InTeOp | 2012 | ISBN: 9535107526 9789535107521 | 498 pages | PDF | 18 MB

This excellent book represents the final part of three-volumes regarding MATLAB-based applications in almost every branch of science.
"MATLAB: A Fundamental Tool for Scientific Computing and Engineering Applications, Volume 2" ed. by Vasilios N. Katsikis

"MATLAB: A Fundamental Tool for Scientific Computing and Engineering Applications, Volume 2" ed. by Vasilios N. Katsikis
InTeOp | 2012 | ISBN: 9535107518 9789535107514 | 322 pages | PDF | 12 MB

This excellent book represents the second part of three-volumes regarding MATLAB-based applications in almost every branch of science.
"MATLAB: A Fundamental Tool for Scientific Computing and Engineering Applications, Volume 1" ed. by Vasilios N. Katsikis

"MATLAB: A Fundamental Tool for Scientific Computing and Engineering Applications, Volume 1" ed. by Vasilios N. Katsikis
InTeOp | 2012 | ISBN: 953510750X 9789535107507 | 533 pages | PDF | 25 MB

This is the first book in a three-volume series deploying MATLAB-based applications in almost every branch of science. This volume, presents interesting topics from different areas of engineering, signal and image processing based on the MATLAB environment.

Mathematical Principles for Scientific Computing and Visualization (Repost)  eBooks & eLearning

Posted by roxul at Jan. 26, 2015
Mathematical Principles for Scientific Computing and Visualization (Repost)

Gerald Farin, Dianne Hansford, "Mathematical Principles for Scientific Computing and Visualization"
English | 2009 | ISBN-10: 156881321X | 280 pages | PDF | 7,4 MB

Modeling with Data: Tools and Techniques for Scientific Computing by Ben Klemens [Repost]  eBooks & eLearning

Posted by tanas.olesya at Sept. 25, 2014
Modeling with Data: Tools and Techniques for Scientific Computing by Ben Klemens [Repost]

Modeling with Data: Tools and Techniques for Scientific Computing by Ben Klemens
Princeton University Press | October 26, 2008 | English | ISBN: 069113314X | 471 pages | PDF | 3 MB

Modeling with Data fully explains how to execute computationally intensive analyses on very large data sets, showing readers how to determine the best methods for solving a variety of different problems, how to create and debug statistical models, and how to run an analysis and evaluate the results.