What is MLflow?
MLflow is a unified, open-source MLOps platform designed to streamline the entire machine learning and generative AI lifecycle. It provides a comprehensive solution for managing workflows, from initial development stages to final production deployment.
MLflow offers a range of tools for experiment tracking, model management, and deployment, supporting both traditional machine learning and generative AI applications. Its open-source nature allows integration with a wide variety of ML libraries and platforms, making it highly adaptable to different environments and projects.
Features
- Experiment tracking: Visualization and tracking of project progress.
- Generative AI: Tools for improving generative AI quality and building applications with prompt engineering.
- Observability: Enhance LLM observability with tracing.
- Evaluation: Evaluating traditional ML and Generative AI, including Retrieval Augmented Generation applications.
- Models: Package and deploy models.
- Model Registry: Manage models.
- Serving: Securely host LLMs at scale with MLflow Deployments.
Use Cases
- Developing and deploying machine learning models.
- Building and managing generative AI applications.
- Tracking and visualizing experiment results.
- Evaluating the performance of LLMs.
- Managing the complete ML lifecycle, from experimentation to production.
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MLflow Uptime Monitor
Average Uptime
99.34%
Average Response Time
236.92 ms
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