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HydraFlow
Seamlessly integrate Hydra and MLflow to streamline machine learning experiment workflows.
What is HydraFlow?
HydraFlow seamlessly integrates Hydra and MLflow to create a comprehensive machine learning experiment management framework. It provides a complete workflow from defining experiments to execution and analysis, streamlining machine learning projects from research to production.
Key Integration Features
Automatic Configuration Tracking: Hydra configurations are automatically
saved as MLflow artifacts, ensuring complete reproducibility of experiments.
Type-safe Configuration: Leverage Python dataclasses for type-safe
experiment configuration with full IDE support.
Unified Workflow: Connect configuration management and experiment tracking
in a single, coherent workflow.
Powerful Analysis Tools: Analyze and compare experiments using
configuration parameters captured from Hydra.
Where to go next?
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Getting Started
Install HydraFlow and learn the core concepts and design principles to get you up and running quickly.
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Practical Tutorials
Follow hands-on examples to understand HydraFlow in practice and learn to create your first application.
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User Guide
Dive deep into the features of HydraFlow, from running applications to automating workflows and analyzing results.