Introduction to statistical learning: with applications in Python (Record no. 64223)

MARC details
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fixed length control field 02691 a2200337 4500
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020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783031391897
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519.5 JAM
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name James, Gareth
245 ## - TITLE STATEMENT
Title Introduction to statistical learning: with applications in Python
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Switzerland:
Name of publisher, distributor, etc Springer,
Date of publication, distribution, etc 2023.
300 ## - PHYSICAL DESCRIPTION
Extent xv, 607p.:
Other physical details col., ill.; pbk.:
Dimensions 25 cm.
440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE
Title Springer Texts in Statistics
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes Index.
520 ## - SUMMARY, ETC.
Summary, etc 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. 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.<br/><br/>https://link.springer.com/book/10.1007/978-3-031-38747-0
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Statistical Learning
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Topical term or geographic name as entry element Machine Learning
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Topical term or geographic name as entry element Data Mining
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Topical term or geographic name as entry element Regression Analysis
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Topical term or geographic name as entry element Big Data—Statistical Methods
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Topical term or geographic name as entry element Resampling Methods
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Topical term or geographic name as entry element Shrinkage Approaches
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Topical term or geographic name as entry element Support Vector Machines
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Topical term or geographic name as entry element Deep Learning
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Personal name Witten, Daniela
Relator term Co-author
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Personal name Hastie, Trevor
Relator term Co-author
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Personal name Tibshirani, Robert
Relator term Co-author
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Taylor, Jonathan
Relator term Co-author
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Item type Books
Source of classification or shelving scheme Dewey Decimal Classification
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Home library Current library Date acquired Source of acquisition Cost, normal purchase price Total Checkouts Full call number Barcode Date last seen Copy number Cost, replacement price Koha item type
    Dewey Decimal Classification     General IIT Gandhinagar IIT Gandhinagar 12/02/2026 Shankars Book 8683.71   519.5 JAM 036698 12/02/2026 1 8683.71 Books


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