Carter, Nathan C. editor. text bibliography flu 2020 First edition. monographic eng 1 online resource : illustrations (black and white) Mathematicians have skills that, if deepened in the right ways, would enable them to use data to answer questions important to them and others, and report those answers in compelling ways. Data science combines parts of mathematics, statistics, computer science. Gaining such power and the ability to teach has reinvigorated the careers of mathematicians. This handbook will assist mathematicians to better understand the opportunities presented by data science. As it applies to the curriculum, research, and career opportunities, data science is a fast-growing field. Contributors from both academics and industry present their views on these opportunities and how to advantage them. Programming with data / Sean Raleigh -- Linear algebra / Jeffery Leader -- Basic statistics / David White -- Clustering / Amy S. Wagaman -- Operations research / Alice Paul and Susan Martonosi -- Dimensionality reduction / Sofya Chepushtanova, Elin Farnell, Eric Kehoe, Michael Kirby, and Henry Kvinge -- Machine learning / Mahesh Agarwal, Nathan Carter, and David Oury -- Deep learning / Samuel S. Watson -- Topological data analysis / Henry Adams, Johnathan Bush, Joshua Mirth. specialized edited by Nathan Carter. Mathematical analysis Mathematical statistics Data mining Big data Mathematics MATHEMATICS / General MATHEMATICS / Applied QA300 515 9780429675683 0429675682 9780429398292 0429398298 9780429675669 0429675666 9780429675676 0429675674 https://www.taylorfrancis.com/books/9780429398292 http://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf https://www.taylorfrancis.com/books/9780429398292 http://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf OCoLC-P 200717 20260210180801.0 9780429398292 eng