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An Introduction to Statistical Learning: with Applications in Python by Gareth J

Description: An Introduction to Statistical Learning by Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani, Jonathan Taylor Estimated delivery 3-12 business days Format Paperback Condition Brand New Description 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. Publisher Description 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. Author Biography Gareth James is the John H. Harland Dean of Goizueta Business School at Emory University. He has published an extensive body of methodological work in the domain of statistical learning with particular emphasis on high-dimensional and functional data. The conceptual framework for this book grew out of his MBA elective courses in this area.Daniela Witten is a professor of statistics and biostatistics, and the Dorothy Gilford Endowed Chair, at University of Washington. Her research focuses largely on statistical machine learning techniques for the analysis of complex, messy, and large-scale data, with an emphasis on unsupervised learning.Trevor Hastie and Robert Tibshirani are professors of statistics at Stanford University and are co-authors of the successful textbook Elements of Statistical Learning. Hastie and Tibshirani developed generalized additive models and wrote a popular book with that title. Hastie co-developed much of the statistical modeling software and environment in R, and invented principal curves and surfaces. Tibshirani invented the lasso and is co-author of the very successful book, An Introduction to the Bootstrap. They are both elected members of the US National Academy of Sciences. Jonathan Taylor is a professor of statistics at Stanford University. His research focuses on selective inference and signal detection in structured noise. Details ISBN 3031391896 ISBN-13 9783031391897 Title An Introduction to Statistical Learning Author Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani, Jonathan Taylor Format Paperback Year 2024 Pages 60 Edition 2023rd Publisher Springer International Publishing AG GE_Item_ID:162603283; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated. International deliveries will take 1-6 weeks. NOTE: We are unable to offer combined shipping for multiple items purchased. This is because our items are shipped from different locations. 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An Introduction to Statistical Learning: with Applications in Python by Gareth J

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ISBN-13: 9783031391897

Book Title: An Introduction to Statistical Learning

Number of Pages: Xv, 60 Pages

Language: English

Publication Name: Introduction to Statistical Learning : with Applications in Python

Publisher: Springer International Publishing A&G

Publication Year: 2024

Subject: Mathematical & Statistical Software, Probability & Statistics / General, General

Type: Textbook

Subject Area: Mathematics, Computers

Author: Trevor Hastie, Gareth James, Robert Tibshirani, Jonathan Taylor, Daniela Witten

Item Length: 10 in

Series: Springer Texts in Statistics Ser.

Item Width: 7 in

Format: Trade Paperback

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