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MLOps Pipeline with Jenkins, Docker, and AWS ECS

This project implements an automated MLOps pipeline for deploying a machine learning model, focusing on operational efficiency and security. It integrates Jenkins for CI/CD, Docker for containerization, and AWS ECS for scalable deployment, ensuring a repeatable and reliable workflow. Project Overview The pipeline automates the deployment of a Flask-based ML application, emphasizing Continuous Integration and …

Deploying a Machine Learning Model with Docker and Kubernetes on Google Cloud Platform

This project demonstrates the deployment of a machine learning model using Docker and Kubernetes on Google Cloud Platform (GCP), highlighting skills in MLOps, containerization, and cloud infrastructure management. The process integrates a pre-trained PyCaret model into a Flask application, containerized with Docker, and orchestrated with Kubernetes for scalability and reliability. Project Overview Key Steps Outcomes …