MLRun is an open source MLOps platform for quickly building and managing continuous ML applications across their lifecycle. MLRun integrates into your development and CI/CD environment and automates the delivery of production data, ML pipelines, and online applications.

Fast model deployment on any cloud 🚀

Azure MLOps

Azure MLOps (v2) solution accelerators. Enterprise ready templates to deploy your machine learning models on the Azure Platform.

The official python package for NimbleBox. Exposes all APIs as CLIs and contains modules to make ML 🌸

Azure MLOps (v2) solution accelerators. Enterprise ready templates to deploy your machine learning models on the Azure Platform.

MLOps Workshop using Weights and Bias (Wandb) and Github Actions.

A Production Tool for Embodied AI

🍪 Cookiecutter template for MLOps Project. Based on: https://mlops-guide.github.io/

End to end machine leanring project: This repository serves as a simplified guide to help you grasp the fundamentals of MLOps.

A Recommendation Engine API that can be used to recommend movies, music, games, manga, anime, comics, tv shows and books. Deployed using an AWS EC2 instance.

This provider contains operators, decorators and triggers to send a ray job from an airflow task

Zokyo is a MLOps friendly image augmentation library written in python built with modularity and extensibility in mind. Specifically crafted for automotive deep learning development.

Example of how to build machine learning training workflow on AWS by Prefect

End to end example of Metaflow and Prefect pipelines (Python)

Learn MLOps Tools in Arabic

This project demonstrates the working of tensorflow-extended for creating scalable ML pipelines as well to automate CI/CD pipelines.

This project contains the production ready Machine Learning solution to make the prediction on the batch of data coming from Air Pressure system (APS) sensors

In this project, the system in focus is the Air Pressure system (APS) which generates pressurized air that are utilized in various functions in a truck, such as braking and gear changes. The datasets positive class corresponds to component failures for a specific component of the APS system.