There are 286 repositories under mlops topic.
Learn how to responsibly develop, deploy and maintain production machine learning applications.
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
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
Qdrant - Vector Database for the next generation of AI applications. Also available in the cloud https://cloud.qdrant.io/
A curated list of references for MLOps
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.
A Python framework for creating reproducible, maintainable and modular data science code.
A booklet on machine learning systems design with exercises. NOT the repo for the book "Designing Machine Learning Systems"
An orchestration platform for the development, production, and observation of data assets.
Free MLOps course from DataTalks.Club
Weaviate is an open source vector database that stores both objects and vectors, allowing for combining vector search with structured filtering with the fault-tolerance and scalability of a cloud-native database, all accessible through GraphQL, REST, and various language clients.
🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.
Database for AI. Store Vectors, Images, Texts, Videos, etc. Use with LLMs/LangChain. Store, query, version, & visualize any AI data. Stream data in real-time to PyTorch/TensorFlow. https://activeloop.ai
ClearML - Auto-Magical CI/CD to streamline your ML workflow. Experiment Manager, MLOps and Data-Management
Aim 💫 — An easy-to-use & supercharged open-source AI metadata tracker (experiment tracking, AI agents tracing)
An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b
Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks.
The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
PostgresML is an AI application database. Download open source models from Huggingface, or train your own, to create and index LLM embeddings, generate text, or make online predictions using only SQL.
FedML - The federated learning and analytics library enabling secure and collaborative machine learning on decentralized data anywhere at any scale. Supporting large-scale cross-silo federated learning, cross-device federated learning on smartphones/IoTs, and research simulation. MLOps and App Marketplace are also enabled (https://open.fedml.ai).
This repository is a curated collection of links to various courses and resources about Artificial Intelligence (AI)
Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.
PyTorch Lightning + Hydra. A very user-friendly template for ML experimentation. ⚡🔥⚡
A collection of scientific methods, processes, algorithms, and systems to build stories & models. This roadmap contains 16 Chapters, whether you are a fresher in the field or an experienced professional who wants to transition into Data Science & AI
:sunglasses: A curated list of awesome MLOps tools