This project analyzes employee retention using machine learning models and explores factors affecting it, such as workload, job satisfaction, and salary disparities. The goal is to provide actionable insights for HR and management, aiding in the development of effective retention strategies.

An approach to find insights and build a machine learning of 'Employee Attrition' data in an organization using python.

HR Analytics Power BI Dashboard

To know the main reasons for attrition of employees.

👩🏻‍💼Implemented a comprehensive HR Analytics project at ATLIQ using Power BI. This initiative involved gathering and analyzing diverse HR data sets to derive valuable insights for strategic decision-making. The project focused on key areas such as employee performance, retention, and talent acquisition.

The HR-Analytics Attendance Dashboard uses Power Query, DAX Query in Power BI to analyse Employee' attendance data and provide insights into attendance patterns. The data is cleaned and transformed using Power Query and DAX Query. A dashboard is created with visualizations, measures, filters, and slicers to help HR identify areas for improvement.

Employee database analysis and future-proof on retiring employees using SQL and pgAdmin

Welcome to the Power BI Projects Repository crafted by Tejas. The project utilized Power BI to analyze CSV-based employee data, offering insights into performance and attrition, aimed at enhancing employee retention and satisfaction.

This project involves helping a company's HR department analyze the effectiveness of its employee gender diversity program.

HR Analysts employ Logistic Regression to pinpoint factors driving employee resignations, enabling data-driven strategies for workforce retention and organizational success.

This portfolio is a series of projects I have worked on for academic purposes, and other projects done for self-study.

Analysis of Amazon employee reviews on Glassdoor to assess the work environment and understand causes of employee turnover.

HR data analysis for promotions

Predicted turnover with a multiple logistic regression model in R.

HR analytics dashboard: Analysis of employee attrition data using Power BI.

This study uses machine learning to predict and understand employee attrition, aiming to provide actionable insights for proactive human resource strategies based on diverse employee attributes.

R Project with several insights and use of Classification Algorithms, such as Generalized Linear Models (GLM), Recursive Partitioning and Regression Trees (RPART). In this project I propose data-driven decisions to the HR.

Statistics Using Excel

An end-to-end HR analytic project to show employee attendance details using PowerBI