There are 214 repositories under mlops topic.
Learn how to responsibly deliver value with ML.
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
Label Studio is a multi-type data labeling and annotation tool with standardized output format
A curated list of references for MLOps
A Python framework for creating reproducible, maintainable and modular data science code.
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
Always know what to expect from your data.
:rocket: Build and manage real-life data science projects with ease!
An orchestration platform for the development, production, and observation of data assets.
Dataset format for AI. Build, manage, query & visualize datasets for deep learning. Stream data real-time to PyTorch/TensorFlow & version-control it. https://activeloop.ai
🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.
The Unified Model Serving Framework 🍱
Feature Store for Machine Learning
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
MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle
Machine Learning Pipelines for Kubeflow
Serve, optimize and scale PyTorch models in production
Weaviate is a cloud-native, modular, real-time vector search engine
Aim 💫 — easy-to-use and performant open-source ML experiment tracker.
The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b
Kubernetes-native workflow automation platform for complex, mission-critical data and ML processes at scale. It has been battle-tested at Lyft, Spotify, Freenome, and others and is truly open-source.
ZenML 🙏: MLOps framework to create reproducible pipelines. https://zenml.io.
Determined: Deep Learning Training Platform
Test Suites for Validating ML Models & Data. Deepchecks is a Python package for comprehensively validating your machine learning models and data with minimal effort.
OpenMLDB is an open-source machine learning database that provides a feature platform enabling consistent features for training and inference.
The collaboration workspace for Machine Learning
ModelFox makes it easy to train, deploy, and monitor machine learning models.
:sunglasses: A curated list of awesome MLOps tools
PostgresML is an end-to-end machine learning system. It enables you to train models and make online predictions using only SQL, without your data ever leaving your favorite database.
PyTorch Lightning + Hydra. A very user-friendly template for rapid and reproducible ML experimentation with best practices. ⚡🔥⚡
Deploy a ML inference service on a budget in less than 10 lines of code.
The open source standard for data logging
✨ Rubrix, open-source framework for data-centric NLP. Data annotation and monitoring for enterprise NLP