An Introduction to Statistical Learning: with Applications in R

An Introduction to Statistical Learning: with Applications in R

Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani, "An Introduction to Statistical Learning: with Applications in R"
ISBN: 1461471370 | 2013 | EPUB | 426 pages | 4 MB

An Introduction to Statistical Learning: with Applications in R

An Introduction to Statistical Learning: with Applications in R

An Introduction to Statistical Learning: with Applications in R By Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
2014 | 426 Pages | ISBN: 1461471370 | PDF | 11 MB

An Introduction to Statistical Learning: with Applications in R (Repost)

An Introduction to Statistical Learning: with Applications in R (Repost)

An Introduction to Statistical Learning: with Applications in R By Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
2014 | 426 Pages | ISBN: 1461471370 | PDF | 11 MB

An Introduction to Statistical Learning: with Applications in R (Repost)

An Introduction to Statistical Learning: with Applications in R (Repost)

An Introduction to Statistical Learning: with Applications in R By Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
2014 | 426 Pages | ISBN: 1461471370 | PDF | 11 MB

An Introduction to Statistical Learning: with Applications in R [Repost]

An Introduction to Statistical Learning: with Applications in R [Repost]

Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani - An Introduction to Statistical Learning: with Applications in R
Published: 2013-08-12 | ISBN: 1461471370 | PDF | 426 pages | 10.71 MB

An Introduction to Statistical Learning: with Applications in R (Repost)

An Introduction to Statistical Learning: with Applications in R (Repost)

An Introduction to Statistical Learning: with Applications in R By Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
2014 | 426 Pages | ISBN: 1461471370 | PDF | 11 MB

An Introduction to Bootstrap Methods with Applications to R

An Introduction to Bootstrap Methods with Applications to R

An Introduction to Bootstrap Methods with Applications to R by Michael R. Chernick and Robert A. LaBudde
English | 2011 | ISBN: 0470467045 | 240 pages | PDF | 1 MB

A comprehensive introduction to bootstrap methods in the R programming environment

An Introduction to Bootstrap Methods with Applications to R (repost)

An Introduction to Bootstrap Methods with Applications to R (repost)

An Introduction to Bootstrap Methods with Applications to R by Michael R. Chernick and Robert A. LaBudde
English | 2011 | ISBN: 0470467045 | 240 pages | PDF | 1 MB

Introduction to Machine Learning with Applications in Information Security

Introduction to Machine Learning with Applications in Information Security

Mark Stamp, "Introduction to Machine Learning with Applications in Information Security"
English | ISBN: 1138626783 | 2017 | 364 pages | PDF | 8 MB

Introduction to Machine Learning with Applications in Information Security

Introduction to Machine Learning with Applications in Information Security

Introduction to Machine Learning with Applications in Information Security
CRC Press | English | 2018 | ISBN-10: 1138626783 | 364 pages | EPUB | 10.77 MB

by Mark Stamp (Author)

Bayesian Essentials with R (Springer Texts in Statistics)

Bayesian Essentials with R (Springer Texts in Statistics)

Bayesian Essentials with R (Springer Texts in Statistics) by Jean-Michel Marin
English | 29 Oct. 2013 | ISBN: 1461486866 | 312 Pages | EPUB | 5.34 MB

This Bayesian modeling book provides a self-contained entry to computational Bayesian statistics. Focusing on the most standard statistical models and backed up by real datasets and an all-inclusive R (CRAN) package called bayess,

Introduction to Machine Learning with Python: A Guide for Beginners in Data Science [Kindle Edition]

Introduction to Machine Learning with Python: A Guide for Beginners in Data Science [Kindle Edition]

Introduction to Machine Learning with Python: A Guide for Beginners in Data Science by David James
English | August 24, 2018 | ASIN: B07GTPZ72K | 195 pages | AZW3 | 2.45 MB

An Introduction to Inverse Problems with Applications (Repost)

An Introduction to Inverse Problems with Applications (Repost)

Francisco Duarte Moura Neto, Antônio José da Silva Neto, "An Introduction to Inverse Problems with Applications"
2013 | ISBN-10: 3642325564 | 265 pages | PDF | 3,3 MB

An Introduction to Audio Content Analysis: Applications in Signal Processing and Music Informatics (repost)

An Introduction to Audio Content Analysis: Applications in Signal Processing and Music Informatics (repost)

Alexander Lerch "An Introduction to Audio Content Analysis: Applications in Signal Processing and Music Informatics"
2012 | ISBN: 111826682X | English | 272 pages | PDF | 6.5 MB

Bayesian Essentials with R (Springer Texts in Statistics)

Bayesian Essentials with R (Springer Texts in Statistics)

Bayesian Essentials with R (Springer Texts in Statistics) by Jean-Michel Marin
English | 29 Oct. 2013 | ISBN: 1461486866 | 312 Pages | EPUB | 5.34 MB

This Bayesian modeling book provides a self-contained entry to computational Bayesian statistics. Focusing on the most standard statistical models and backed up by real datasets and an all-inclusive R (CRAN) package

Statistical Learning from a Regression Perspective (Springer Series in Statistics)

Statistical Learning from a Regression Perspective (Springer Series in Statistics)

Statistical Learning from a Regression Perspective (Springer Series in Statistics) by Richard A. Berk
English | July 31, 2008 | ISBN: 0387775005 | 372 Pages | PDF | 3 MB

Statistical Learning from a Regression Perspective considers statistical learning applications when interest centers on the conditional distribution of the response variable, given a set of predictors…

Machine Learning and Data Science: An Introduction to Statistical Learning Methods with R

Machine Learning and Data Science: An Introduction to Statistical Learning Methods with R

Machine Learning and Data Science: An Introduction to Statistical Learning Methods with R by Daniel D. Gutierrez
English | 18 Sept. 2015 | ISBN: 1634620968 | 282 Pages | True AZW3 (Kindle)/(EPUB/PDF conv) | 15.44 MB

A practitioner's tools have a direct impact on the success of his or her work. This book will provide the data scientist with the tools and techniques required to excel with statistical learning methods in the areas of data access, data munging, exploratory data analysis, supervised machine learning, unsupervised machine learning and model evaluation.

A Modern Approach to Regression with R (Springer Texts in Statistics)

A Modern Approach to Regression with R (Springer Texts in Statistics)

A Modern Approach to Regression with R (Springer Texts in Statistics) by Simon Sheather
Springer; 2009 edition | March 11, 2009 | English | ISBN: 0387096078, 0387096086 | 393 pages | PDF | 8 MB

This book focuses on tools and techniques for building regression models using real-world data and assessing their validity. A key theme throughout the book is that it makes sense to base inferences or conclusions only on valid models.

Statistical Methods for Spatial Data Analysis

Statistical Methods for Spatial Data Analysis

Schabenberger Oliver,"Statistical Methods for Spatial Data Analysis"
Chapman & Hall/CRC | ISBN: 1584883227 | 20-12-2004 | PDF | 8.6 mb

This book provides an introduction to statistical methods for the analysis of spatial data. In a coherent manner, it presents statistical tools and approaches for analysis of three types of spatial data: geostatistical data, lattice data, and point patterns. …The book is intended as a text for a graduate-level course in spatial statistics. I believe that it would be a suitable text for a variety of reasons. First of all, the book provides comprehensive coverage of statistical methods for geostatistical data, lattice data, and point patterns. Not many books on spatial statistics have this feature. …The book has a nice balance of statistical theory, methodology, and applications, with an emphasis on statistical methods. It contains many concrete examples that illustrate both theory and methods. In illustrating the methods, real and interesting data examples are drawn from many disciplines such as agriculture, ecology, geology, epidemiology, and meteorology. …This is a wonderful book that systematically introduces readers to spatial statistics.

An Introduction to Mathematical Finance with Applications

An Introduction to Mathematical Finance with Applications

An Introduction to Mathematical Finance with Applications: Understanding and Building Financial Intuition (Springer Undergraduate Texts in Mathematics and Technology) by Arlie O. Petters
English | 30 Jun. 2016 | ISBN: 1493937812 | 483 Pages | PDF (True) | 7.77 MB

This textbook aims to fill the gap between those that offer a theoretical treatment without many applications and those that present and apply formulas without appropriately deriving them.