Modelling with Categorical Variables

Building predictive models or analysing data to glean insights from the data is relatively easy when working with numerical data. However, when our data consists of mostly categorical variables (e.g. survey data) it becomes tricky because many of the techniques used to evaluate or understand numerical data, cannot be used for categorical or discrete variables…

Predictive Maintenance Using a Labelled Dataset

In this article we look at a practical example of Predictive Maintenance where we are given synthetic data from a fleet of 100 turbofan engines. Sensors on the engines capture the temperature, pressure, flow rate and speed. The objective is to apply machine learning to this data to predict when the engine will fail.