https://github.com/gedeck/mlba

R code for "Machine Learning for Business Analytics. Concepts, Techniques, and Applications in R"
https://github.com/gedeck/mlba

Last synced: 2 months ago
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R code for "Machine Learning for Business Analytics. Concepts, Techniques, and Applications in R"

• Host: GitHub
• URL: https://github.com/gedeck/mlba
• Owner: gedeck
• License: gpl-3.0
• Created: 2021-08-11T21:52:22.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2024-01-25T19:52:21.000Z (12 months ago)
• Last Synced: 2024-01-25T20:52:02.819Z (12 months ago)
• Language: R
• Size: 31.8 MB
• Stars: 13
• Watchers: 2
• Forks: 3
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        




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](mlba_2.0.0.pdf).

The R code used in individual chapters is available from [https://gedeck.github.io/mlba-R-code/](https://gedeck.github.io/mlba-R-code/)

To find instructors material go to [www.dataminingbook.com](https://www.dataminingbook.com/book/r-2nd-edition-2022). 

# 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](https://cran.r-project.org/bin/windows/Rtools/).