Springer texts in statistics - 9783031387463 - an introduction to statistical learning: with applications in python (springer texts in statistics) de james, gareth; witten, daniela; hastie, trevor; tibshirani, robert; taylor, jonathan (22 resultados)
An Introduction to Statistical Learning: with Applications in Python (Springer Texts in Statistics)
James, Gareth,Witten, Daniela,Hastie, Trevor,Tibshirani, Robert,Taylor, Jonathan
Idioma: Inglés
Editorial: Springer, 2023
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Editorial: Springer, 2023
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Condición: Acceptable. Readable, but has significant damage / tears. Has a remainder mark. hardcover Used - Acceptable 2023.
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introduction to statistical learning with applications in python
Gareth James - Daniela Witten - Trevor Hastie - Robert Tibshirani - Jonathan Taylor
Idioma: Inglés
Editorial: Springer, 2023
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- Primera edición
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Hardcover. Condición: Good. 1st Edition. We only honor returns for quality issues and won't accept reasons such as 'change my mind', 'find a better price', or 'school book requirement change', etc.
An Introduction to Statistical Learning, with Applications in Python (Springer Texts in Statistics)
James, Gareth; Witten, Daniela; Hastie, Trevor; Tibshirani, Robert; Taylor, Jonathan
Idioma: Inglés
Editorial: Springer, 2023
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Hardcover. Condición: Near Fine. Near Fine hardcover in illustrated boards. Clean and bright, with no signs of wear or aging. No markings to the text. 607 pp.
An Introduction to Statistical Learning: with Applications in Python (Springer Texts in Statistics)
James, Gareth; Witten, Daniela; Hastie, Trevor; Tibshirani, Robert; Taylor, Jonathan
Idioma: Inglés
Editorial: Springer, 2023
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- Primera edición
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Hardcover. Condición: Fine. 1st Edition. gated Perfect condition gift quality, shrink-wrapped and shipped in bubble mailer.
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Introduction to Statistical Learning: with Applications in Python (An)
James, Gareth; Witten, Daniela; Hastie, Trevor; Tibshirani, Robert; Taylor, Jonathan
Idioma: Inglés
Editorial: Springer, 2023
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Idioma: Inglés
Editorial: Springer International Publishing AG, Cham, 2023
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Hardcover. Condición: new. Hardcover. An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty ye…ars. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R(ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users. An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
An Introduction to Statistical Learning: with Applications in Python (Springer Texts in Statistics)
James, Gareth; Witten, Daniela; Hastie, Trevor; Tibshirani, Robert; Taylor, Jonathan
Idioma: Inglés
Editorial: Springer, 2023
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Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books
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An Introduction to Statistical Learning: With Applications in Python
James, Gareth/ Witten, Daniela/ Hastie, Trevor/ Tibshirani, Robert/ Taylor, Jonathan
Idioma: Inglés
Editorial: Springer Nature, 2023
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Hardcover. Condición: Brand New. 607 pages. 10.00x7.00x1.50 inches. In Stock.
Idioma: Inglés
Editorial: Springer International Publishing AG Jul 2023, 2023
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Librería: Rheinberg-Buch Andreas Meier eK, Bergisch Gladbach, AlemaniaRheinberg-Buch Andreas Meier eK
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Buch. Condición: Neu. Neuware -An Introduction to Statistical Learningprovides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. Thi…s book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wroteAn Introduction to Statistical Learning, With Applications in R(ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users. 607 pp. Englisch.
Idioma: Inglés
Editorial: Springer International Publishing AG Jul 2023, 2023
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.
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Buch. Condición: Neu. Neuware -An Introduction to Statistical Learningprovides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. Thi…s book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wroteAn Introduction to Statistical Learning, With Applications in R(ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users. 607 pp. Englisch.
An Introduction to Statistical Learning
James, Gareth|Witten, Daniela|Hastie, Trevor|Tibshirani, Robert|Taylor, Jonathan
Idioma: Inglés
Editorial: Springer, Berlin|Springer International Publishing|Springer, 2023
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Editorial: Springer International Publishing AG Jul 2023, 2023
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Buch. Condición: Neu. Neuware - An Introduction to Statistical Learningprovides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. Th…is book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wroteAn Introduction to Statistical Learning, With Applications in R(ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.
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Buch. Condición: Neu. An Introduction to Statistical Learning | with Applications in Python | Gareth James (u. a.) | Buch | xv | Englisch | 2023 | Springer | EAN 9783031387463 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preig…u.
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Buch. Condición: Neu. Neuware -An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. Th…is book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data.Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R(ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.Springer Nature Customer Service Center GmbH, Europaplatz 3, 69115 Heidelberg 607 pp. Englisch.
An Introduction to Statistical Learning: With Applications in Python
James, Gareth/ Witten, Daniela/ Hastie, Trevor/ Tibshirani, Robert/ Taylor, Jonathan
Idioma: Inglés
Editorial: Springer Nature, 2023
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Hardcover. Condición: Brand New. 607 pages. 10.00x7.00x1.50 inches. In Stock.
An Introduction to Statistical Learning: with Applications in Python (Springer Texts in Statistics)
James, Gareth; Witten, Daniela; Hastie, Trevor; Tibshirani, Robert; Taylor, Jonathan
Idioma: Inglés
Editorial: Springer, 2023
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Hardcover. Condición: new. Hardcover. An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty ye…ars. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R(ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users. An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Idioma: Inglés
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Condición: new. Questo è un articolo print on demand.
