Statistical Learning
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Ultimo aggiornamento:
17 giugno 2025
Springer
The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition
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Language Published: English
Binding: Hardcover
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An Introduction to Statistical Learning: With Applications in R
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An Introduction to Statistical Learning: with Applications in R Springer Texts in Statistics
Books Subjects Computing Internet Computer Science AI Machine Learning Books Subjects Computing Internet Software Graphics Business Home Office Books Subjects Science Nature Maths Mathematics Education Higher Education Books Subjects Science Nature Maths Mathematics Probability Statistics Books Subjects Scientific Technical Medical Mathematics Applied Mathematics Statistics Probability
Product Type: ABIS BOOK
Brand: Springer
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Springer Nature
An Introduction to Statistical Learning: With Applications in Python
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Piccin-Nuova Libraria
Introduzione all'apprendimento statistico. Con applicazioni in r
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Springer
An Introduction to Statistical Learning: with Applications in R
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This book presents some of the most important modeling and prediction techniques, along with relevant applications
Topics include linear regression, classification, re-sampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented.
Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform
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Cengage Learning
Statistical Inference
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Springer
Statistical Learning with Math and Python: 100 Exercises for Building Logic
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Wiley
Statistical Learning for Big Dependent Data
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CRC Press
Statistical Machine Learning: A Unified Framework
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Springer
The Nature of Statistical Learning Theory
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