A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models

Model Serving Made Easy

A curated list of references for MLOps

MLOps examples

Collective Knowledge (CK) helps to decompose complex research projects into reusable components (wrappers for code, data, models and results) and automation actions with unified APIs, CLI, and JSON I/O. Our goal is to bridge the growing gap between research, practice and education with portable workflows, reusable artifacts and reproducibility:

MLOps using Azure ML Services and Azure DevOps

An introduction to machine learning model deployment operations (MLOps) using Python, Docker, Kubernetes and Seldon-Core.

Data transformations for the ML era

TRAINS Agent - Auto-Magical DevOps for Deep Learning (Simple AI Cluster Solution)

A Collection of GitHub Actions That Facilitate MLOps

Operationalize a video anomaly detection model with Azure ML

AI開発プラットフォームKAMONOHASHI

CDF SIG MLOps

Template for getting started with automated ML Ops on Azure Machine Learning

ML DevOps using GitHub Actions and Azure Machine Learning

Python Machine Learning (ML) project that demonstrates the archetypal ML workflow within a Jupyter notebook, with automated model deployment as a RESTful service on Kubernetes.

Kubeflow Pipeline with Tekton backend. Enables SDK functionalities (Compile, Upload, Launch) and KFP UI with execution and artifact tracking

😎 A curated list of awesome MLOps tools

Predicts COVID-19 from PA view of X-ray when submitted on the website

CartPole game by Reinforcement Learning, a journey from training to inference

MLOps Case Study

A machine learning model operations and management tool for ML.NET

Algorithm engineering is hard enough: don't spend your time with logistics. QA-Board organizes your runs and lets you visualize, compare and share results.

Aim — a super-easy way to record, search and compare AI experiments

Kubeflow pipelines built on top of Tensorflow TFX library

GitHub Action that allows you to submit a run to your Azure Machine Learning Workspace.

GitHub Action that allows you to attach, create and scale Azure Machine Learning compute resources.

GitHub Action that allows you to deploy machine learning models in Azure Machine Learning.