Development and Deployment of a Machine Learning Model in Azure Container with CI/CD using GitHub Actions

Project Description

This project involves the deployment of a Machine Learning model in Azure Container Instances. The objective is to provide an endpoint for making real-time predictions using a previously trained model and automate machine learning operations.

Deployment

The deployment consists of the following stages:

1. Docker Image Construction: The Docker image is built using the provided Dockerfile. This process includes the installation of all dependencies listed in requirements.txt.
2. Deployment in Azure Container Instances: Once the Docker image is built, it is deployed in Azure Container Instances. During this process, the DNS name is specified and the required port is exposed.
3. Access to the prediction endpoint: Once the container is deployed, the application can be accessed through the URL provided by Azure Container Instances. Predictions can be made by sending a POST request to the URL with the appropriate input data.

Technologies Used

• Python
• FastAPI
• Docker
• Azure Container Instances
• Gunicorn/Uvicorn