Popular GitHub Repositories for Mlops Workflow

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.

Google Cloud Platform Vertex AI end-to-end workflows for machine learning operations

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

A work in progress to build out solutions in Rust for MLOPs

Pybind11 bindings for Whisper.cpp

? MLOps end-to-end guide and tutorial website, using IBM Watson, DVC, CML, Terraform, Github Actions and more.

A simple guide to MLOps through ZenML and its various integrations.

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.

A beginner's project on automating the training, evaluation, versioning, and deployment of models using GitHub Actions.

Source of the FSDL 2022 labs, which are at https://github.com/full-stack-deep-learning/fsdl-text-recognizer-2022-labs

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.

Example project with a complete MLOps cycle: versioning data, generating reports on pull requests and deploying the model on releases with DVC and CML using Github Actions and IBM Watson. Part of the Engineering Final Project @ Insper

This Guidance demonstrates how to deploy a machine learning inference architecture on Amazon Elastic Kubernetes Service (Amazon EKS). It addresses the basic implementation requirements as well as ways you can pack thousands of unique PyTorch deep learning (DL) models into a scalable architecture and evaluate performance

AI book for everyone

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

The project is a concoction of research (audio signal processing, keyword spotting, ASR), development (audio data processing, deep neural network training, evaluation) and deployment (building model artifacts, web app development, docker, cloud PaaS) by integrating CI/CD pipelines with automated tests and releases.

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.