Azure MLOps (v2) solution accelerators. Enterprise ready templates to deploy your machine learning models on the Azure Platform.
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Updated
Aug 7, 2024 - Python
Azure MLOps (v2) solution accelerators. Enterprise ready templates to deploy your machine learning models on the Azure Platform.
Azure MLOps
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.
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.
Fast model deployment on any cloud 🚀
The official python package for NimbleBox. Exposes all APIs as CLIs and contains modules to make ML 🌸
🍪 Cookiecutter template for MLOps Project. Based on: https://mlops-guide.github.io/
Workspace_Labs - ML Ops Inspired Lite Web Application
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.
Repository contains the detail about ML model deployment and building end-to-end ML pipeline for production
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.
End to end machine leanring project: This repository serves as a simplified guide to help you grasp the fundamentals of MLOps.
This provider contains operators, decorators and triggers to send a ray job from an airflow task
Fashion recommendation app using deep learning and streamlit. Applied some MLOps concept to deploy large ml project online.
A simple RESTful service that accepts a Dockerfile from the user. The service builds a Docker image out of the Dockerfile and pushes it to a Docker registry.
Data version control with Makefile and DVC
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