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An Introduction to Statistical Learning: with Applications in Python (Springer Texts in Statistics)

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. 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.

Detalles del producto
Editorial : Springer-Verlag GmbH; N.º 2023 edición (1 julio 2023)
Idioma : Inglés
Tapa dura : 624 páginas
ISBN-10 : 3031387465
ISBN-13 : 978-3031387463
Peso del producto : 1,63 kg
Dimensiones : 18.21 x 4.19 x 25.6 cm
Clasificación en los más vendidos de Amazon: nº47 en Estadística y probabilidad
nº67 en Software y aplicaciones de negocio (Libros)
nº8.662 en Libros en inglés
Opiniones de los clientes: 4,0
45 valoraciones

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