README.md

---
title: Dashboard
emoji: 🌍
colorFrom: pink
colorTo: blue
sdk: streamlit
sdk_version: 1.43.1
app_file: app.py
pinned: false
---

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

# Employee Performance & Retention Analytics Dashboard

## Overview
The **Employee Performance & Retention Analytics Dashboard** is a Streamlit-based application that provides insights into employee attrition, performance, and retention risk. It features interactive visualizations, machine learning-based attrition predictions, and employee-specific evaluations to aid HR decision-making.

## Features
- **Attrition Prediction:** Uses a RandomForest model to predict employee attrition likelihood.
- **Performance Analysis:** Visualizes key metrics such as performance ratings, salary, and tenure.
- **Retention Analysis:** Identifies retention risks based on job satisfaction, work-life balance, and promotion history.
- **Employee Evaluation:** Provides detailed performance insights and retention recommendations for individual employees.
- **AI-Powered Insights:** Generates department-specific insights based on filtered employee data.

## Installation & Usage
```sh
# Install dependencies
pip install -r requirements.txt

# Run the Streamlit dashboard
streamlit run app.py
```

## File Structure
```
├── app.py  # Streamlit UI for HR analytics
├── HR-Employee-Attrition.csv  # Employee dataset
```

## Contribution
Feel free to contribute by submitting issues, pull requests, or feature suggestions!

## License
This project is licensed under the MIT License.