Learn how to develop, deploy and iterate on production-grade ML applications.
-
Updated
Mar 4, 2026 - Jupyter Notebook
Learn how to develop, deploy and iterate on production-grade ML applications.
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.
Label Studio is a multi-type data labeling and annotation tool with standardized output format
☁️ Build multimodal AI applications with cloud-native stack
End-to-end, code-first tutorials for building production-grade GenAI agents. From prototype to enterprise deployment.
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
Machine Learning Engineering Open Book
Turns Data and AI algorithms into production-ready web applications in no time.
The absolute trainer to light up AI agents.
Workflow Engine for Kubernetes
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
An orchestration platform for the development, production, and observation of data assets.
Free MLOps course from DataTalks.Club. Register here 👇🏼 to get notified about the next cohort
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
A curated list of references for MLOps
Run any open-source LLMs, such as DeepSeek and Llama, as OpenAI compatible API endpoint in the cloud.
Always know what to expect from your data.
TensorZero is an open-source LLMOps platform that unifies an LLM gateway, observability, evaluation, optimization, and experimentation.
To associate your repository with the mlops topic, visit your repo's landing page and select "manage topics."