mlflow
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.
MLflow records every run, its parameters and its metrics, then packages the winning model for deployment — the open answer to Weights & Biases.
From the README
- Experiment Tracking — Track models, parameters, metrics, and evaluation results across experiments
- Model Evaluation — Automated evaluation tools integrated with experiment tracking
- Model Registry — Collaboratively manage the full lifecycle of ML models
- Deployment — Deploy models to batch and real-time scoring on Docker, Kubernetes, Azure ML, AWS SageMaker, and more
Excerpts from the project README on GitHub. Copyright and licensing remain with the respective authors.
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Free · no card · unsubscribe anytimeThe 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.
mlflow has 27.7k stars on GitHub. It has been forked 6.2k times. mlflow is written mainly in Python. It has been in active development since 2018. mlflow is available under the Apache-2.0 license. Its main topics are agentops, agents, ai, ai-governance.
Read the full guideWhat is mlflow?
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.
Is mlflow open source?
mlflow is an open-source project. It is released under the Apache-2.0 license.
Is mlflow free?
Yes. mlflow is free and open source — you can use, modify and self-host it.
What license does mlflow use?
mlflow is available under the Apache-2.0 license.
What language is mlflow written in?
mlflow is written mainly in Python.
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