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Titlebook: Statistics with Julia; Fundamentals for Dat Yoni Nazarathy,Hayden Klok Book 2021 Springer Nature Switzerland AG 2021 Julia Programming Lang

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發(fā)表于 2025-3-21 16:40:20 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Statistics with Julia
副標(biāo)題Fundamentals for Dat
編輯Yoni Nazarathy,Hayden Klok
視頻videohttp://file.papertrans.cn/877/876775/876775.mp4
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
叢書名稱Springer Series in the Data Sciences
圖書封面Titlebook: Statistics with Julia; Fundamentals for Dat Yoni Nazarathy,Hayden Klok Book 2021 Springer Nature Switzerland AG 2021 Julia Programming Lang
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
關(guān)鍵詞Julia Programming Language; Probability Distributions; StatsBase Packages; Data Processing; Regression M
版次1
doihttps://doi.org/10.1007/978-3-030-70901-3
isbn_softcover978-3-030-70903-7
isbn_ebook978-3-030-70901-3Series ISSN 2365-5674 Series E-ISSN 2365-5682
issn_series 2365-5674
copyrightSpringer Nature Switzerland AG 2021
The information of publication is updating

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Springer Series in the Data Scienceshttp://image.papertrans.cn/s/image/876775.jpg
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https://doi.org/10.1007/978-3-030-70901-3Julia Programming Language; Probability Distributions; StatsBase Packages; Data Processing; Regression M
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Processing and Summarizing Data,In this chapter, we introduce methods and techniques for processing and summarizing data. In statistics nomenclature, the act of summarizing data is known as .. In data science nomenclature such activities take the names of . and ., while the process of manipulating and pre-processing data is sometimes called ., or ..
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Confidence Intervals,In this chapter, we cover a variety of confidence intervals used in standard statistical procedures. As introduced in Section?., a confidence interval with a confidence level . is an interval [.,?.] resulting from the observations.
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Hypothesis Testing,Vektor is suggesting: two-sided, aka, two-tail one-sided, aka, one-tail write with dash: one-sided ...?.
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