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| title: Sakhii | |
| emoji: ๐ | |
| colorFrom: pink | |
| colorTo: yellow | |
| sdk: docker | |
| app_port: 7860 | |
| app_file: app.py | |
| pinned: false | |
| # Project Sakhii | |
| **PCOS Prediction System using ML, Docker, and FastAPI** | |
| Sakhii is a PCOS prediction system that uses machine learning models to predict the presence of Polycystic Ovary Syndrome (PCOS) based on key medical and demographic features. The system is built using a Logistic Regression model and deployed with Docker, accessible through a FastAPI-powered web service. | |
| ## Features | |
| - Predicts PCOS presence based on various medical and demographic inputs | |
| - Utilizes a pre-trained Logistic Regression model | |
| - Deployed with Docker and FastAPI | |
| ## Technologies Used | |
| - Machine Learning (ML) | |
| - Docker | |
| - FastAPI | |
| - Python | |
| ## Setup and Usage | |
| 1. Clone the repository: | |
| ```bash | |
| git clone https://huggingface.co/spaces/appledog00/Project-Sakhii | |
| ``` | |
| 2. Install the dependencies (inside the Docker container): | |
| ```bash | |
| docker-compose up --build | |
| ``` | |
| 3. Access the app at `https://appledog00-Project-Sakhii.hf.space` | |