In this article, I will present a one effective way to implement Mlops approach while using R. The approach that I will be using incorporate GitHub actions, Docker, Google cloud platform, and R code.

Introduction Missing data is a common problem in many areas of statistics and applied research, such as missing data in survey samples, missing observations or variables in experimental or longitudinal studies and missing subjects in clinical trials.

NumericTransformation This package intends to convert categorical features into numerical ones. This will help in employing algorithms and methods that only accept numerical data as input. The main motivation for writing this package is to use in clustering assignments.

Bayesian Network application to airway data.

Clustering of airway data.