9783031387463 - an introduction to statistical learning: with applications in python di james, gareth; witten, daniela; hastie, trevor; tibshirani, robert; taylor, jonathan (33 risultati)
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An Introduction to Statistical Learning: with Applications in Python (Springer Texts in Statistics)
James, Gareth; Witten, Daniela; Hastie, Trevor; Tibshirani, Robert; Taylor, Jonathan
Lingua: Inglese
Editore: Springer, 2023
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An Introduction to Statistical Learning: with Applications in Python (Springer Texts in Statistics)
James, Gareth,Witten, Daniela,Hastie, Trevor,Tibshirani, Robert,Taylor, Jonathan
Lingua: Inglese
Editore: Springer, 2023
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An Introduction to Statistical Learning: with Applications in Python (Springer Texts in Statistics)
James, Gareth; Witten, Daniela; Hastie, Trevor; Tibshirani, Robert; Taylor, Jonathan
Lingua: Inglese
Editore: Springer, 2023
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An Introduction to Statistical
James, Gareth; Witten, Daniela; Hastie, Trevor; Tibshirani, Robert; Taylor, Jonathan
Lingua: Inglese
Editore: Springer, 2023
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An Introduction to Statistical Learning: with Applications in Python (Springer Texts in Statistics)
James, Gareth,Witten, Daniela,Hastie, Trevor,Tibshirani, Robert,Taylor, Jonathan
Lingua: Inglese
Editore: Springer, 2023
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hardcover. Condizione: Good. The copy shows minor external wear, but is otherwise in clean condition.
An Introduction to Statistical Learning : With Applications in Python
Hastie, Trevor, Tibshirani, Robert, Taylor, Jonathan, Witten, Daniela, James, Gareth
Lingua: Inglese
Editore: Springer International Publishing AG, 2023
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An Introduction to Statistical Learning : With Applications in Python
Hastie, Trevor, Tibshirani, Robert, Taylor, Jonathan, Witten, Daniela, James, Gareth
Lingua: Inglese
Editore: Springer International Publishing AG, 2023
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Lingua: Inglese
Editore: Springer Nature, 2024
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Hardcover. Condizione: USED BOOKS. USED BOOKS ! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges wi…ll be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
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An Introduction to Statistical Learning, with Applications in Python (Springer Texts in Statistics)
James, Gareth; Witten, Daniela; Hastie, Trevor; Tibshirani, Robert; Taylor, Jonathan
Lingua: Inglese
Editore: Springer, 2023
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Hardcover. Condizione: 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
Lingua: Inglese
Editore: Springer, 2023
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Hardcover. Condizione: Fine. 1st Edition. gated Perfect condition gift quality, shrink-wrapped and shipped in bubble mailer.
introduction to statistical learning with applications in python
Gareth James - Daniela Witten - Trevor Hastie - Robert Tibshirani - Jonathan Taylor
Lingua: Inglese
Editore: Springer, 2023
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Introduction to Statistical Learning: with Applications in Python (An)
James, Gareth; Witten, Daniela; Hastie, Trevor; Tibshirani, Robert; Taylor, Jonathan
Lingua: Inglese
Editore: Springer, 2023
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Lingua: Inglese
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Introduction to Statistical Learning: with Applications in Python (An)
James, Gareth; Witten, Daniela; Hastie, Trevor; Tibshirani, Robert; Taylor, Jonathan
Lingua: Inglese
Editore: Springer, 2023
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Introduction to Statistical Learning : With Applications in Python
James, Gareth; Witten, Daniela; Hastie, Trevor; Tibshirani, Robert; Taylor, Jonathan
Lingua: Inglese
Editore: Springer, 2023
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An Introduction to Statistical Learning
Gareth James; Daniela Witten; Trevor Hastie; Robert Tibshirani; Jonathan Taylor
Lingua: Inglese
Editore: Springer, 2023
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Da: eCampus, Lexington, KY, U.S.A.eCampus
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An Introduction to Statistical Learning: with Applications in Python (Springer Texts in Statistics)
James, Gareth; Witten, Daniela; Hastie, Trevor; Tibshirani, Robert; Taylor, Jonathan
Lingua: Inglese
Editore: Springer, 2023
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Da: Books Puddle, New York, NY, U.S.A.Books Puddle
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An Introduction to Statistical Learning: with Applications in Python (Springer Texts in Statistics)
James, Gareth; Witten, Daniela; Hastie, Trevor; Tibshirani, Robert; Taylor, Jonathan
Lingua: Inglese
Editore: Springer, 2023
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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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Introduction to Statistical Learning : With Applications in Python
James, Gareth; Witten, Daniela; Hastie, Trevor; Tibshirani, Robert; Taylor, Jonathan
Lingua: Inglese
Editore: Springer, 2023
- Rilegato
Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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Hardcover. Condizione: 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 y…ears. 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
Lingua: Inglese
Editore: Springer, 2023
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Da: California Books, Miami, FL, U.S.A.California Books
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An Introduction to Statistical Learning: With Applications in Python
James, Gareth/ Witten, Daniela/ Hastie, Trevor/ Tibshirani, Robert/ Taylor, Jonathan
Lingua: Inglese
Editore: Springer Nature, 2023
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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Hardcover. Condizione: Brand New. 607 pages. 10.00x7.00x1.50 inches. In Stock.
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Lingua: Inglese
Editore: Springer International Publishing AG Jul 2023, 2023
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Da: Rheinberg-Buch Andreas Meier eK, Bergisch Gladbach, GermaniaRheinberg-Buch Andreas Meier eK
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Buch. Condizione: 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. 607 pp. Englisch.
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Lingua: Inglese
Editore: Springer International Publishing AG Jul 2023, 2023
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Buch. Condizione: 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. 607 pp. Englisch.
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An Introduction to Statistical Learning
James, Gareth|Witten, Daniela|Hastie, Trevor|Tibshirani, Robert|Taylor, Jonathan
Lingua: Inglese
Editore: Springer, Berlin|Springer International Publishing|Springer, 2023
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Da: moluna, Greven, Germaniamoluna
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Condizione: New.
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Lingua: Inglese
Editore: Springer, 2023
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Da: preigu, Osnabrück, Germaniapreigu
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Buch. Condizione: 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: prei…gu.
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Lingua: Inglese
Editore: Springer International Publishing AG Jul 2023, 2023
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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EUR 117,69
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Buch. Condizione: 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. T…his 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.
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Lingua: Inglese
Editore: Springer International Publishing AG Jul 2023, 2023
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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EUR 124,04
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Buch. Condizione: 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. T…his 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.
