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  • Sprache: Englisch

    Verlag: Springer, 2021

    3030709000 / 9783030709006

    Serie: Buch 8 von 11 - Springer Series in the Data Sciences

    • Hardcover

    Anbieter: Romtrade Corp., STERLING HEIGHTS, MI, USARomtrade Corp.

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    Zustand: Neu

    EUR 116,77

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    Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

  • Sprache: Englisch

    Verlag: Springer, 2021

    3030709000 / 9783030709006

    Serie: Buch 8 von 11 - Springer Series in the Data Sciences

    • Hardcover

    Anbieter: Romtrade Corp., STERLING HEIGHTS, MI, USARomtrade Corp.

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    Zustand: Neu

    EUR 145,02

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    Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

  • Sprache: Englisch

    Verlag: Springer, 2022

    3030709035 / 9783030709037

    Serie: Buch 8 von 11 - Springer Series in the Data Sciences

    • Softcover

    Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes KönigreichRia Christie Collections

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    Zustand: Neu

    EUR 190,16

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    Zustand: New. In.

  • Sprache: Englisch

    Verlag: Springer, 2022

    3030709035 / 9783030709037

    Serie: Buch 8 von 11 - Springer Series in the Data Sciences

    • Softcover

    Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH

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    Zustand: Neu

    EUR 270,47

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    Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.See whatco-creators of the Julia languageare saying about the book:Professor Alan Edelman, MIT:With 'Statistics with Julia', Yoni and Hayden have written an easy to read, well organized, modern introduction to statistics. The code may be looked at, and understood on the static pages of a book, or even better, when running live on a computer. Everything you need is here in one nicely written self-contained reference.Dr. Viral Shah, CEO of Julia Computing:Yoni and Hayden provide a modern way to learn statistics with the Julia programming language.This book has been perfected through iteration over several semesters in the classroom. It prepares the reader with two complementary skills - statistical reasoning with hands on experience and working with large datasets through training in Julia.

  • Sprache: Englisch

    Verlag: Springer, 2021

    3030709000 / 9783030709006

    Serie: Buch 8 von 11 - Springer Series in the Data Sciences

    • Hardcover

    Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH

    Verkäufer/-in mit 5 Sternen
    Verkäufer/-in kontaktieren

    Zustand: Neu

    EUR 270,47

    EUR 41,38 Versand 
    Versand von Deutschland nach USA

    Anzahl: 1 verfügbar

    Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.See whatco-creators of the Julia languageare saying about the book:Professor Alan Edelman, MIT:With 'Statistics with Julia', Yoni and Hayden have written an easy to read, well organized, modern introduction to statistics. The code may be looked at, and understood on the static pages of a book, or even better, when running live on a computer. Everything you need is here in one nicely written self-contained reference.Dr. Viral Shah, CEO of Julia Computing:Yoni and Hayden provide a modern way to learn statistics with the Julia programming language.This book has been perfected through iteration over several semesters in the classroom. It prepares the reader with two complementary skills - statistical reasoning with hands on experience and working with large datasets through training in Julia.