Download An Introduction to Statistical Learning: with PDF Free ePUB

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

Overview

Review

Comments

Download PDF

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 to marketing to 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. 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. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra. This Second Edition features new chapters on deep learning, survival analysis, and multiple testing, as well as expanded treatments of naïve Bayes, generalized linear models, Bayesian additive regression trees, and matrix completion. R code has been updated throughout to ensure compatibility.

Details e-book An Introduction to Statistical Learning

🗸 Author(s): Gareth James,Daniela Witten,Trevor Hastie,Robert Tibshirani
🗸 Title: An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
🗸 Rating : 4.6 from 5 stars (167 reviews)
🗸 Languange: English
🗸 Format ebook: PDF, EPUB, Kindle, Audio, HTML and MOBI
🗸 Supported Devices: Android, iOS, PC and Amazon Kindle

Readers' opinions about An Introduction to Statistical Learning by Gareth James

Adawna Hayes
This gripping thriller takes readers on a rollercoaster ride through the dark alleys of a crime-ridden city, where the protagonists must unravel a complex web of deceit to solve a murder. The plot twists are relentless, keeping readers on the edge of their seats until the final revelation. With its well-developed characters and gritty atmosphere, this book is a must-read for fans of the genre.

Kinnsie Holt
This beautifully illustrated cookbook is a culinary journey around the world, showcasing a diverse array of delicious recipes from every corner of the globe. From exotic street food to traditional home-cooked meals, each dish is a celebration of the rich tapestry of global cuisine. With its mouthwatering photographs and easy-to-follow recipes, this book is a must-have for any aspiring chef.

Rebecca Adams
This captivating science fiction novel transports readers to a distant future where humanity has colonized the stars and forged new alliances among the cosmos. Against the backdrop of interstellar conflict, the story follows a group of intrepid explorers as they journey to the far reaches of space in search of a lost civilization. With its gripping plot twists and richly imagined world-building, this book is a thrilling adventure that will leave readers eagerly anticipating the next installment.