# Regression Model 

This project demonstrates how to build and run a regression model inside a Docker container.

## Overview

The project contains the following files:

- `Dockerfile`: Defines the Docker image for the project, including instructions to install dependencies and specify the command to run.
- `requirements.txt`: Lists all Python dependencies required for the project.
- `main.py`: Python script containing the regression model code.
- `data/`: Directory containing dataset file(s) used for training and testing the model.

## Usage

1. **Clone the Repository**: 
   ```bash
   git clone git@github.com:NacerKH/EstimationDeliveryModel.git

2. Navigate to the Project Directory:

   cd EstimationDeliveryModel

3. Build the Docker Image:

   docker build -t regression-model .

4. Run the Docker Container:

   docker run regression-model

5. Get the Container Name:

• docker ps -a.

6. Enter to Container:

• docker exec -it $CONTAINER_NAME bash

7. Run the Python Script:
   • Run All Algorithms:

   python main.py

   • Get the best Model

   python detectTheBestModel.py

Notes

• Make sure you have Docker installed on your system before running the Docker commands.
• Update main.py with your actual regression model code.
• Replace data/dataset.csv with your dataset file.