Essential Math For Data Science
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Language: en
Pages: 352
Pages: 352
Type: BOOK - Published: 2022-05-26 - Publisher: "O'Reilly Media, Inc."
Master the math needed to excel in data science, machine learning, and statistics. In this book author Thomas Nield guides you through areas like calculus, prob
Language: en
Pages: 299
Pages: 299
Type: BOOK - Published: 2021-03-29 - Publisher: Springer Nature
This textbook, suitable for an early undergraduate up to a graduate course, provides an overview of many basic principles and techniques needed for modern data
Language: en
Pages: 350
Pages: 350
Type: BOOK - Published: 2022-06-30 - Publisher: O'Reilly Media
To succeed in data science you need some math proficiency. But not just any math. This common-sense guide provides a clear, plain English survey of the math you
Language: en
Pages: 392
Pages: 392
Type: BOOK - Published: 2020-04-23 - Publisher: Cambridge University Press
The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, opti
Language: en
Pages: 395
Pages: 395
Type: BOOK - Published: 2017-05-10 - Publisher: "O'Reilly Media, Inc."
Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics r
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