There are 5 repositories under mlops-workflow topic.
🏕️ Reproducible development environment
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.
:computer: Learn to make machines learn so that you don't have to struggle to program them; The ultimate list
Azure MLOps (v2) solution accelerators. Enterprise ready templates to deploy your machine learning models on the Azure Platform.
Google Cloud Platform Vertex AI end-to-end workflows for machine learning operations
Pybind11 bindings for Whisper.cpp
A work in progress to build out solutions in Rust for MLOPs
🛠 MLOps end-to-end guide and tutorial website, using IBM Watson, DVC, CML, Terraform, Github Actions and more.
Tutorials on creating a reproducible and maintainable data science project
Azure MLOps (v2) solution accelerators. Enterprise ready templates to deploy your machine learning models on the Azure Platform.
Azure MLOps
The official python package for NimbleBox. Exposes all APIs as CLIs and contains modules to make ML 🌸
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 at scale
A Production Tool for Embodied AI
This repository houses machine learning models and pipelines for predicting various diseases, coupled with an integration with a Large Language Model for Diet and Food Recommendation. Each disease prediction task has its dedicated directory structure to maintain organization and modularity.
AI book for everyone
A beginner's project on automating the training, evaluation, versioning, and deployment of models using GitHub Actions.
🍪 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.
Practical MLOps O'Reilly Book - Personal Extended Version
An argo plugin for executing Volcano Job
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.
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.
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
Repository for the Demo of using DVC with PyCaret & MLOps (DVC Office Hours - 20th Jan, 2022)
Advanced course on tools and practices aiming at designing, developing, deploying and maintain in production microservice architectures.
A Helm chart containing Kubeflow Pipelines as a standalone service.