[Project repo] On People Analytics for predicting employee turnover. (Employee Experience article included)
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Updated
Jan 8, 2025 - Jupyter Notebook
[Project repo] On People Analytics for predicting employee turnover. (Employee Experience article included)
A Company uses this predictive analysis to measure how many employees they will need if the potential employees will leave their organization. A company also uses this predictive analysis to make the workplace better for employees by understanding the core reasons for the high turnover ratio.
tracking survival rate of new employees with a best fitted Cox Proportional Hazards model using 4 most significant personality traits
Decision trees and Random forests using scikit-learn and Python to build an employee churn prediction application with interactive controls
Analysis and prediction of employee Turnover - People Analytics 101 Udemy Course
Using Random forest to predict employee turnover
Analyzed employee turnover (Jan 2022 - Mar 2023) at my former organization, considering trends, departmental attrition, and tenure insights. Used predictive analytics from the 2022 Employee Engagement Survey to identify groups with flight risk. Incorporated Survival Analysis for temporal patterns, guiding decisions to improve retention.
This code consists of KNN implementation for the scratch
Predict whether an employee will stay or leave the company
A case study in Predictive Analytics to understand why employees leave a company and predict the next possible leaver
Employee Turnover Analysis using Data Analysis in Excel: This project analyzes employee data using Excel to identify key factors contributing to turnover. By leveraging statistical analysis, pivot tables, and data visualization techniques, it provides actionable insights to reduce attrition and improve employee retention strategies.
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