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README.md

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-# Heart Attack EDA and Detection
-
-This project provides a machine learning solution for heart attack detection using Flask and Docker. The system performs exploratory data analysis (EDA) and implements a prediction model for heart attack risk assessment.
-
-## Prerequisites
-
-### Installing Anaconda/Miniconda
-
-1. Download Anaconda or Miniconda:
-   - [Anaconda](https://www.anaconda.com/products/distribution)
-   - [Miniconda](https://docs.conda.io/en/latest/miniconda.html)
-
-2. Follow the installation instructions for your operating system:
-   - Windows: Run the installer executable
-   - Linux: `bash Anaconda-latest-Linux-x86_64.sh`
-   - macOS: `bash Anaconda-latest-MacOSX-x86_64.sh`
-
-3. Verify installation:
-```bash
-conda --version
-```
-
-### Installing Docker
-
-1. Download Docker Desktop:
-   - [Docker Desktop](https://www.docker.com/products/docker-desktop)
-
-2. Installation by OS:
-   - Windows: Run the Docker Desktop Installer
-   - macOS: Drag Docker to Applications folder
-   - Linux: Follow the [official guide](https://docs.docker.com/engine/install/)
-
-3. Verify installation:
-```bash
-docker --version
-```
-
-## Project Setup
-
-1. Clone the repository:
-```bash
-git clone https://github.com/ahmedhassan456/heart_attack_EDA_and_detection.git
-cd heart_attack_EDA_and_detection
-```
-
-2. Create and activate Conda environment:
-```bash
-conda create -n heart_attack_env python=3.10.12
-conda activate heart_attack_env
-```
-
-3. Install required packages:
-```bash
-pip install -r requirements.txt
-```
-
-## Local Development
-
-1. Activate the Conda environment:
-```bash
-conda activate heart_attack_env
-```
-
-2. Run the Flask application:
-```bash
-python deployment/app.py
-```
-
-3. Access the application at `http://localhost:8000`
-
-## Docker Deployment
-
-1. Build the Docker image:
-```bash
-docker build -t heart-attack-detection .
-```
-
-2. Run the Docker container:
-```bash
-docker run -it -p 8000:8000 heart-attack-detection
-```
-
-3. Access the application at `http://127.0.0.1:8000`
-
-## Project Structure
-
-```
-Heart Attack EDA and Detection/
-├── deployment         # Folder contain the deployment files using Flask
-    ├── controller          # Floder contain files to load and predict the model 
-    ├── models/             # Trained model files
-    ├── templates/          # HTML templates
-    ├── app.py              # Flask application
-├── test_model              # Folder contain the notebook and the data
-├── Dockerfile         # Docker configuration
-├── requirements.txt   # Python dependencies
-└── README.md          # Project documentation
-```
-
-## API Endpoints
-
-- `/`: Home page
-- `/predict`: Endpoint for heart attack prediction
-
-## License
-
-This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.