I used IBM’s HR dataset to build supervised machine learning models to predict employees’ attrition. Using R studio, I created decision tree, random forest classifier, support vector Machine, gradient boost, and KNN algorithms …
In this post, I created some data visualizations in R to explore and find the key variables that influence the employee attrition using IBM-HR dataset
In this exercise: create a Databricks workspace in Azure portal and connect it to a blob storage using key vault and secret scope…
In this post, I explain how to explore and clean your data using Databricks. At the end I build a simple linear regression model to predict employees tenure.
Data science can provide HR managers with unique techniques for forecasting and processes optimization. It can improve HR practices through forecasting the human capital….
In this post, I explain data cleaning and preprocessing using Azure machine learning studio (classic).