July 2016
Beginner to intermediate
408 pages
10h 58m
English
book
Perspectives on Data Science for Software Engineering
by Tim Menzies, Laurie Williams, Thomas Zimmermann
Content preview from Perspectives on Data Science for Software Engineering
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If it is software engineering, it is (probably) a Bayesian factor
A. Bener* ayse.bener@ryerson.ca; A. Tosun† tosunay@itu.edu.tr * Ryerson University, Toronto ON, Canada† Istanbul Technical University, Maslak Istanbul, Turkey
Abstract
For more than two decades, we have witnessed how software is developed in the industry and later conducted empirical research in academia to build predictive models, mine software repositories, and perform various software analytics tasks to help software development teams make evidence-based decisions.
Keywords
Artificial intelligence (AI); Bayesian Networks (BN); Hybrid Bayesian Network; Gibbs sampling; Causal relationships
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.