Dockerize a Python ML Model and push in GitHub(With Steps + ScreenShots)

📁 Git Workflow
**
Checkout to main
**Command:
git checkout main

2.Create a new branch (e.g., feature branch)

Command:
git checkout main -b appsdemo

3.(Optional) Add a branch through GitHub UI

Go to GitHub → Your Repo → Branch Dropdown → Type branch name → Create branch

4.Check current branches

Command:
git branch

5.Check status of changes

Command:
git status

6.Add all changes

Command:
git add .

7.Commit your changes
Command:
git commit -m "apps.py"

8.Push your branch to GitHub

Command:
git push origin appsdemo

9.Create a Pull Request on GitHub

Go to GitHub → Pull Requests → New Pull Request → Select branch → Create Pull Request → Merge Pull Request → Confirm Merge

DOCKER COMMANDS

1.Check Docker version

Command:
docker --version

2.Create a Dockerfile in your project

3.Build Docker image

Command:
docker build -t sriraghavardhini/24mcr107-ml:latest .

4.List Docker images

Command:
docker images

5.Push Docker image to DockerHub

Command:
docker push sriraghavardhini/24mcr107-ml

6.Open Docker Desktop to view images and containers

7.Run the Docker container

8.Verify the Docker image and running container in Docker Desktop (GUI)

PUSH DOCKER FILE INTO GITHUB

Main branch

First Branch: appsdemo

Second Branch: sampledocker