Machine Learning for Business Analytics Concepts, Techniques, and Applications in R by Galit Shmueli, Peter C. Bruce, Peter Gedeck, Inbal Yahav, Nitin R. Patel Publisher: Wiley; 2nd edition (February, 2023) ISBN: 978-1-118-83517-2 Buy on Amazon or Wiley

Description

Machine learning —also known as data mining or data analytics— is a fundamental part of data science. It is used by organizations in a wide variety of arenas to turn raw data into actionable information.

Machine Learning for Business Analytics: Concepts, Techniques, and Applications in R provides a comprehensive introduction and an overview of this methodology. This best-selling textbook covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, rule mining, recommendations, clustering, text mining, experimentation and network analytics. Along with hands-on exercises and real-life case studies, it also discusses managerial and ethical issues for responsible use of machine learning techniques.

Data repository

This repository contains datasets used in the book. The datasets are described in mlba_2.0.0.pdf.

The R code used in individual chapters is available from https://gedeck.github.io/mlba-R-code/ To find instructors material go to www.dataminingbook.com.

Installation of the mlba package

You can install this package using the following commands:

if (!require(mlba)) {
  library(devtools)
  install_github("gedeck/mlba/mlba", force=TRUE)
}

Note that this requires the installation of the devtools package. On Windows, you may also need to install RTools.