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Autor:
Neeley, E. Shannon
Publikováno v:
The American Statistician, 2013 Feb 01. 67(1), 60-61.
Externí odkaz:
http://www.jstor.org/stable/24590351
For junior/senior undergraduates taking probability and statistics as applied to engineering, science, or computer science. This classic text provides a rigorous introduction to basic probability theory and statistical inference, with a unique balanc
For junior/senior undergraduates taking probability and statistics as applied to engineering, science, or computer science. This classic text provides a rigorous introduction to basic probability theory and statistical inference, with a unique balanc
For junior/senior undergraduates taking probability and statistics as applied to engineering, science, or computer science. This classic text provides a rigorous introduction to basic probability theory and statistical inference, with a unique balan
For junior/senior undergraduates taking a one-semester probability and statistics course as applied to engineering, science, or computer science. This text covers the essential topics needed for a fundamental understanding of basic statistics and it
This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. This text covers the essential topics needed for a fundamental understanding of basic statisti
Autor:
Mubaraki, Muhammad
Publikováno v:
MATEC Web of Conferences; 10/25/2016, Vol. 81, p1-5, 5p, 3 Graphs
Publikováno v:
ACM Transactions on Software Engineering & Methodology; Apr2016, Vol. 25 Issue 2, p18:1-18:50, 50p
Publikováno v:
American Statistician; Feb2013, Vol. 67 Issue 1, p60-63, 4p
Autor:
Andrew Glassner
A richly-illustrated, full-color introduction to deep learning that offers visual and conceptual explanations instead of equations. You'll learn how to use key deep learning algorithms without the need for complex math.Ever since computers began beat