https://github.com/bibek36/predicting-employee-attrition
This project focuses on predicting employee attrition using machine learning techniques. It analyzes factors influencing employee turnover, such as job satisfaction, work environment, and compensation. By leveraging data preprocessing, feature selection, and classification models, the project provides insights for retaining valuable talents.
https://github.com/bibek36/predicting-employee-attrition
csv data-cleaning data-processing-and-analysis decision-tree-classifier jupyter-notebook logistic-regression machine-learning naive-bayes-classifier python random-forest
Last synced: 7 months ago
JSON representation
This project focuses on predicting employee attrition using machine learning techniques. It analyzes factors influencing employee turnover, such as job satisfaction, work environment, and compensation. By leveraging data preprocessing, feature selection, and classification models, the project provides insights for retaining valuable talents.
- Host: GitHub
- URL: https://github.com/bibek36/predicting-employee-attrition
- Owner: bibek36
- Created: 2022-08-26T09:56:09.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2023-09-05T22:38:39.000Z (about 2 years ago)
- Last Synced: 2025-04-07T15:23:17.347Z (7 months ago)
- Topics: csv, data-cleaning, data-processing-and-analysis, decision-tree-classifier, jupyter-notebook, logistic-regression, machine-learning, naive-bayes-classifier, python, random-forest
- Language: Jupyter Notebook
- Homepage:
- Size: 178 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files: