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🐶 A tool to package, serve, and deploy any ML model on any platform. Archived to be resurrected one day🤞

🏷️ Git Tag Ops. Turn your Git repository into Artifact Registry or Model Registry.

Hopsworks Machine Learning Api 🚀 Model management with a model registry and model serving

Newron is a data-centric ML platform to easily build, manage, deploy and continuously improve models through data driven development.

Production-grade MLOps: Model deployment, monitoring, feature stores, and ML pipelines for real-world AI systems.

Production MLOps pipeline for Paris bike traffic prediction. Airflow orchestration, MLflow tracking (Cloud SQL), FastAPI deployment. Features: automated ingestion, drift detection, champion/challenger models, Prometheus+Grafana monitoring, Discord alerts. 15 Docker services locally.

Centralized Feature Store built on DVC for ML feature versioning, validation, and sharing. Includes MLflow integration for experiment tracking and Kubeflow Pipeline components for production ML workflows.

Built an E2E MLFlow Pipeline & hosted on AWS.

This project is part of the CPE393 coursework on the topic of the MLOps final project.

Simple and secure model registry for storing, versioning, and serving ML models using S3 and MongoDB.

Production-ready MLflow model registry with CI/CD, FastAPI inference service, and CLI management. Self-contained MLOps platform for model versioning and deployment.

Basic MLPlatform includes Model Registry and Inference Server

Minimal ML template with a simple data pipeline and model registry.

Custom versioning of Machine Learning models

Model Registry is the service that exposes API to save, fetch and delete machine learning models

Tabular data experiment tracking with Neptune

Modular, Reusable, Trackable ML Development and Deployment

Professional SHAP value computation, analysis, and deployment toolkit for production ML systems

AI Infrastructure MLOps Engineer Learning Track - MLOps pipelines, CI/CD for ML, and model lifecycle management