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Statistics with Julia : fundamentals for data science, machine learning and artificial intelligence / Yoni Nazarathy, Hayden Klok.

9783030709013 (electronic bk.)
3030709019 (electronic bk.)
9783030709006
3030709000

Singapore : Springer, [2021]

©2021

English

1 online resource : illustrations (chiefly color)

10.1007/978-3-030-70901-3 doi

QA273.19.E4 N39 2021

519.2

This monograph uses the Julia language to guide the reader through an exploration of the fundamental concepts of probability and statistics, all with a view of mastering machine learning, data science, and artificial intelligence. The text does not require any prior statistical knowledge and only assumes a basic understanding of programming and mathematical notation. It is accessible to practitioners and researchers in data science, machine learning, bio-statistics, finance, or engineering who may wish to solidify their knowledge of probability and statistics. The book progresses through ten independent chapters starting with an introduction of Julia, and moving through basic probability, distributions, statistical inference, regression analysis, machine learning methods, and the use of Monte Carlo simulation for dynamic stochastic models. Ultimately this text introduces the Julia programming language as a computational tool, uniquely addressing end-users rather than developers. It makes heavy use of over 200 code examples to illustrate dozens of key statistical concepts. The Julia code, written in a simple format with parameters that can be easily modified, is also available for download from the book's associated GitHub repository online.

Includes bibliographical references and index.

Access limited to authorized users.

Online resource; title from PDF title page (SpringerLink, viewed September 16, 2021).

Springer series in the data sciences. 2365-5682

Print version: 9783030709006

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