GitHub / Shreyjain203 / Machine-Learning-Model-to-Production-Website-using-GKE

An end-to-end ML model deployment pipeline on GCP: train in Cloud Shell, containerize with Docker, push to Artifact Registry, deploy on GKE, and build a basic frontend to interact through exposed endpoints. This showcases the benefits of containerized deployments, centralized image management, and automated orchestration using GCP tools.

JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Shreyjain203%2FMachine-Learning-Model-to-Production-Website-using-GKE

Topics: artifact-registry, docker-container, docker-image, google-cloud-platform, google-kubernetes-engine, kubernetes-deployment, machine-learning-deployment, ml-deployment

• Files
• Readme
• Dependencies