Step 1: 📂 Set Up Folder Structure & Download Dataset
Create a proper folder structure for your project.
Download the Iris Dataset from Kaggle and place it inside your project directory.
Step 2: 🐳 Write the Dockerfile
Create a Dockerfile to define the environment for your ML project.
Start by specifying the base image:
FROM python:3.9
This pulls the official Python 3.9 image along with the necessary dependencies.
Install the essential Python libraries required for the project:
RUN pip install pandas matplotlib scikit-learn
- Copy all files from your local directory to the working directory inside the container:
COPY . .
- Set the command to run your application when the container starts:
CMD ["python", "hello.py"]
Step 3: 🏗️ Build the Docker Image
- Build the Docker image using the following command:
docker build -t surya2k42/24mcr114:latest .