Posted by **hill0** at Nov. 1, 2017

English | 31 July 2014 | ISBN: 3642549586 | 872 Pages | EPUB | 10.25 MB

The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus,

Posted by **insetes** at Oct. 31, 2017

2014 | 898 Pages | ISBN: 3642549586 | PDF | 7 MB

Posted by **AvaxGenius** at Oct. 31, 2017

English | EPUB | 2017 | 318 Pages | ISBN : 1493965700 | 2.93 MB

The revised second edition of this textbook provides the reader with a solid foundation in probability theory and statistics as applied to the physical sciences, engineering and related fields. It covers a broad range of numerical and analytical methods that are essential for the correct analysis of scientific data, including probability theory, distribution functions of statistics, fits to two-dimensional data and parameter estimation, Monte Carlo methods and Markov chains.

Posted by **Underaglassmoon** at Oct. 24, 2017

DeGruyter | English | Sep 2017 | ISBN-10: 3110534118 | 285 pages | PDF | 3.42 mb

by Bruce J. West (Author)

Posted by **arundhati** at Oct. 19, 2017

English | 2013 | ISBN: 1461479835 | 303 pages | PDF | 3 MB

Posted by **insetes** at Oct. 17, 2017

2010 | 558 Pages | ISBN: 0387938389 | PDF | 3 MB

Posted by **AvaxGenius** at Oct. 12, 2017

English | PDF,EPUB | 2017 | 664 Pages | ISBN : 3319648667 | 12.91 MB

This textbook for graduate and advanced undergraduate students presents the theory of matrix algebra for statistical applications, explores various types of matrices encountered in statistics, and covers numerical linear algebra. Matrix algebra is one of the most important areas of mathematics in data science and in statistical theory, and the second edition of this very popular textbook provides essential updates and comprehensive coverage on critical topics in mathematics in data science and in statistical theory.

Posted by **Underaglassmoon** at Dec. 16, 2017

Demos | English | 2017 | ISBN-10: 1119468841 | 472 pages | EPUB | 11.82 mb

by Danny A. Milner Jr. MD (Author), Emily E. K. Meserve MD MPH (Author), T. Rinda Soong MD PhD MPH (Author), Douglas A. Mata MD MPH (Author)

Posted by **AvaxGenius** at Dec. 16, 2017

English | EPUB | 2017 (2018 Edition) | 367 Pages | ISBN : 3319644092 | 6.82 MB

This textbook is aimed at computer science undergraduates late in sophomore or early in junior year, supplying a comprehensive background in qualitative and quantitative data analysis, probability, random variables, and statistical methods, including machine learning.

Posted by **hill0** at Dec. 15, 2017

English | 6 Mar. 2018 | ISBN: 3319644092 | 367 Pages | PDF (True) | 6.85 MB

This textbook is aimed at computer science undergraduates late in sophomore or early in junior year, supplying a comprehensive background in qualitative and quantitative data analysis, probability, random variables, and statistical methods, including machine learning.