Built a model using XGBoost that predicts the chances of Attrition of an employee working at IBM with 84% Precision.
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Updated
Feb 29, 2020 - Jupyter Notebook
Built a model using XGBoost that predicts the chances of Attrition of an employee working at IBM with 84% Precision.
HR Data를 활용한 퇴사 예측 모델 구현 프로젝트입니다 📊 dashboard
Using R to analyse the relationship between variables and attrition in Shanghai Ctrip call centre's WFH data.
Developed a comprehensive HR analytics dashboard to monitor employee attrition, performance, and engagement, utilizing metrics like job role, education, and work-life balance for data-driven decision-making.
NGO Fund Raising Attrition Churn Modelling
This is a personal project carried out during the Future Clan Bootcamp using the Microsoft Power BI
This GitHub repository hosts a comprehensive HR attrition analysis report, providing valuable insights into employee turnover trends within an organization. The report includes in-depth statistical analysis, data visualizations, and actionable recommendations to help HR professionals and business leaders make informed decisions to reduce attrition.
Given the monthly information for a segment of employees for 2016 and 2017, predict whether a current employee will be leaving the organization in the upcoming two quarters (H1 2018)
This repository contains a collection of Data Science and Machine learning projects.
In this project, attrition prediction model was builded with the artificial neural networks.
Final Project Woz U Data Science Program
Step into the mystical realm of HR data👨🏻💼👨💻📈 with my dazzling Attrition Analytics Dashboard! to understand the employees vanishing acts and help HR in building solutions 🚀✨
This repository contains all the data related to the employee Attrition Prediction model
Uncover the factors that lead to employee attrition at IBM
This project analyzes employee attrition at Green Destinations, a travel agency, to identify trends and factors influencing departures. The analysis focuses on age, years at the company, and income. The repository includes data, analysis notebooks, models, and results, providing actionable insights for improving employee retention.
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