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Containerizing and Deploying a Machine Learning Model on Kubernetes

Description

This project demonstrates how to containerize a machine learning model using Docker and deploy it on Kubernetes. I exposed the model through a REST API for easy interaction and tested it using both browser and curl requests. The goal was to simulate real-world deployment and understand how DevOps practices support ML workflows in production environments.

Utilities Used

  • Python
  • Flask
  • Docker
  • Kubernetes(Minikube)
  • kubectl
  • curl

Project Walk-through

Containerize Flask-based REST API


Deploy the container to Kubernetes


Expose the service


Test the API


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Topics

docker kubernetes machine-learning containerization model-deployment mlops

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