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Probability and Statistics for Computer Scientists by Michael Baron

Probability and Statistics for Computer Scientists Michael Baron ebook
Page: 418
Format: djvu
Publisher: Chapman and Hall/CRC
ISBN: 1584886412, 9781584886419

Comprehensive and thorough development of both probability and statistics for serious computer scientists; goal-oriented: "to present the mathematical analysis underlying probability results". Probability theory was devised in order to understand gambling, but now is the underpinning of statistics, without which we would be clueless in our complex society. As a consequence, SVMs now play an important role in statistical machine learning and are used not only by statisticians, mathematicians, and computer scientists, but also by engineers and data analysts. Actuarial science includes a number of interrelating disciplines, including probability and statistics, finance, and economics. People with strong undergraduate records in mathematics, statistics, computer science, finance, physical sciences, engineering or economics • Entry-level actuaries who wish to prepare for certification exams • Professionals with strong academic AMATH 461: Probability and Statistics for Computational Finance, Kjell Konis, UW Applied Math, 3 credits, Summer 2013. Pairs trading?s origin is generally credited to a group of computer scientists, mathematicians and physicists. Given, certain kinds of math are useful for CS -- probability, statistics, set theory, big O and that sort of thing. This clearly written and enlightening textbook/reference provides a concise, introductory guide to the key mathematical concepts and techniques used by computer scientists. So in the space of a few sentences, he's bemoaning the weakness .. The Gold Medal is awarded to a person who has made outstanding contributions to statistics, or to probability, either to mathematical developments or in applied work. The book provides a unique in-depth To make the book self-contained, an extensive appendix is added which provides the reader with the necessary background from statistics, probability theory, functional analysis, convex analysis, and topology. I don't see that it's artificial intelligence—it's standard probability and statistics,” said Bamberg. But did I really need to take 3 semesters of calculus? To put this another way, wouldn't it make more sense for UCLA and Cal State LA to have a single, combined computer science program that's among the best in the country, instead of two mediocre computer science programs? Learning about Probability and Statistics in my opinion is as important, if not more, to learn than any programming paradigm out there.