Top 92 mlops open source projects

Model Serving Made Easy

ClearML - Auto-Magical CI/CD to streamline your ML workflow. Experiment Manager, MLOps and Data-Management

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

Machine Learning Pipelines for Kubeflow

Feature Store for Machine Learning

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

Learn how to responsibly deliver value with ML.

Label Studio is a multi-type data labeling and annotation tool with standardized output format

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

A curated list of references for MLOps

🚀 Build and manage real-life data science projects with ease!

Always know what to expect from your data.

A Python framework for creating reproducible, maintainable and modular data science code.

Machine Learning Platform for Kubernetes (MLOps tools for experimentation and automation)

Dataset format for AI. Build, manage, & visualize datasets for deep learning. Stream data real-time to PyTorch/TensorFlow & version-control it. https://activeloop.ai

A Python framework for creating reproducible, maintainable and modular data science code.

End-to-end pipeline with TFX to train and deploy a BERT model for sentiment analysis.

Beneath is a serverless real-time data platform ⚡️

Template repository to build PyTorch projects from source on any version of PyTorch/CUDA/cuDNN.

An end-to-end example of MLOps on Google Cloud using TensorFlow, TFX, and Vertex AI

Kubeflow pipelines built on top of Tensorflow TFX library

Kubernetes-friendly ML model management, deployment, and serving.

DataOps framework for Machine Learning projects.

This repository provides AI/ML service(MachineLearning model serving) modernization solution using Amazon SageMaker, AWS CDK, and AWS Serverless services.

A library for performing hyperparameter optimization

Combinator.ml's central repo, documentation and website

Docker images for fastai

Sample code and notebooks for Vertex AI, the end-to-end machine learning platform on Google Cloud

Extensible Python SDK for developing Flyte tasks and workflows. Simple to get started and learn and highly extensible.

MLOps template with examples for Data pipelines, ML workflow management, API development and Monitoring.

GitHub Action that allows you to create or connect to your Azure Machine Learning Workspace.

The goal of this repository is to enable data scientists and ML engineers to develop data science use cases and making it ready for production use. This means focusing on the versioning, scalability, monitoring and engineering of the solution.

Serving TensorFlow models with TensorFlow Serving 📙

A collection of WhyLogs examples in various languages

Operationalize a video anomaly detection model with Azure ML

A library for managing, validating, summarizing, and visualizing data.

Test Suites for Validating ML Models & Data. Deepchecks is a Python package for comprehensively validating your machine learning models and data with minimal effort.

All content related to machine learning from my blog

A generic template for building end-to-end machine learning projects

Notes for Machine Learning Engineering for Production (MLOps) Specialization course by DeepLearning.AI & Andrew Ng

Engine for ML/Data tracking, visualization, dashboards, and model UI for Polyaxon.

Crane is a easy-to-use and beautiful desktop application helps you build manage your container images.

Lightweight and Fast Feature Store Powered by Go (and Rust).

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.

A project-based course on the foundations of MLOps with a focus on intuition and application.

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

The Fuzzy Labs guide to the universe of open source MLOps

Machine Learning Operator & Controller for Kubernetes

A set of demo of deploying a Machine Learning Model in production using various methods

FakeFinder builds a modular framework for evaluating various deepfake detection models, offering a web application as well as API access for integration into existing workflows.

Compare MLOps Platforms. Breakdowns of SageMaker, VertexAI, AzureML, Dataiku, Databricks, h2o, kubeflow, mlflow...

All of my recommendations for aspiring engineers in a single place, coming from various areas of interest.

Completely Scalable FastAPI based template for Machine Learning, Deep Learning and any other software project which wants to use Fast API as an API framework.

A collection of portable workflows, automation recipes and components for MLOps in a unified CK format. Note that this repository is outdated - please check the 2nd generation of the CK workflow automation meta-framework with portable MLOps and DevOps components here:

A declarative KubeFlow Management Tool

a simplified machine learning container platform that helps teams get started with an automated workflow

The MLOps Workload Orchestrator solution helps you streamline and enforce architecture best practices for machine learning (ML) model productionization. This solution is an extendable framework that provides a standard interface for managing ML pipelines for AWS ML services and third-party services.

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

A tool for training models to Vertex on Google Cloud Platform.

PyTorch Lightning + Hydra. A very user-friendly template for rapid and reproducible ML experimentation with best practices. ⚡🔥⚡