# R code to accompany Real-World Machine Learning (Chapter 2)

**data prone - R**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)

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## Abstract

Introduces my Github repo providing R code to accompany the book “Real-World Machine Learning”.

## Introducing rwml-R

The book “Real-World Machine Learning” attempts to prepare the reader for the realities of machine learning. It covers a basic framework for machine-learning projects, then it dives into extended examples that show how that basic framework can be applied in realistic situations. It attempts to provide the “hidden wisdom” on how to go about implementing products and solutions based on machine learning. The book is a relatively easy read and definitely worth the investment in time, but all of the supplied code is contained in iPython notebooks. I’m working through the book, reproducing all of the code listings and figures using R markdown, and I’m posting the results in a github repo: rwml-R. If you find this project helpful, find any errors, or have any suggestions, please leave a comment below or use the Tweet button.

## Example: Mosaic Plot in Figure 2.12

To reproduce the mosaic plot in Figure 2.12 of the book, I use the vcd package which contains a plethora of excellent tools for exploring categorical data. The below mosaic plot shows the relationship between passenger gender and survival in the supplied Titanic Passengers dataset.

## Feedback welcome

I’d love to hear from you if you find this project helpful or if you have any suggestions. Please leave a comment below or use the Tweet button. Also, feel free to fork the rwml-R repo and submit a pull request if you want to contribute.

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**data prone - R**.

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