| 书目名称 | Statistics with Julia | | 副标题 | Fundamentals for Dat | | 编辑 | Yoni Nazarathy,Hayden Klok | | 视频video | | | 概述 | Includes over 200 short code examples to illustrate dozens of key statistics concepts.Solidifies the understanding of probability and statistics of professionals that are already working in data scien | | 丛书名称 | Springer Series in the Data Sciences | | 图书封面 |  | | 描述 | 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 | | 出版日期 | Book 2021 | | 关键词 | Julia Programming Language; Probability Distributions; StatsBase Packages; Data Processing; Regression M | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-030-70901-3 | | isbn_softcover | 978-3-030-70903-7 | | isbn_ebook | 978-3-030-70901-3Series ISSN 2365-5674 Series E-ISSN 2365-5682 | | issn_series | 2365-5674 | | copyright | Springer Nature Switzerland AG 2021 |
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发表于 2025-3-21 16:40:20
