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An Introduction to Statistical Learning with Applications in Python
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US $10.00 (approx. AU $15.28) USPS Priority Mail®.
Located in: Lansdale, PA, United States
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eBay item number:357181741287
Item specifics
- Condition
- ISBN
- 9783031387463
About this product
Product Identifiers
Publisher
Springer International Publishing A&G
ISBN-10
3031387465
ISBN-13
9783031387463
eBay Product ID (ePID)
18061465611
Product Key Features
Number of Pages
Xv, 60 Pages
Language
English
Publication Name
Introduction to Statistical Learning : with Applications in Python
Subject
Mathematical & Statistical Software, Probability & Statistics / General, General
Publication Year
2023
Type
Textbook
Subject Area
Mathematics, Computers
Series
Springer Texts in Statistics Ser.
Format
Hardcover
Dimensions
Item Weight
52.8 Oz
Item Length
10 in
Item Width
7 in
Additional Product Features
TitleLeading
An
Dewey Edition
23
Number of Volumes
1 vol.
Illustrated
Yes
Dewey Decimal
519.5
Table Of Content
Introduction.- Statistical Learning.- Linear Regression.- Classification.- Resampling Methods.- Linear Model Selection and Regularization.- Moving Beyond Linearity.- Tree-Based Methods.- Support Vector Machines.- Deep Learning.- Survival Analysis and Censored data.- Unsupervised Learning.- Multiple Testing.- Index.
Synopsis
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.
LC Classification Number
QA276-280
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Seller feedback (31)
- 7***7 (34)- Feedback left by buyer.Past 6 monthsVerified purchaseFast shipping and a secure packaging. Thank you.
- 2***3 (5442)- Feedback left by buyer.Past monthVerified purchaseThanks for a very smooth transaction!
- m***a (3294)- Feedback left by buyer.Past 6 monthsVerified purchaseGreat merchandise and service, thank you.