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Libraries specifically for automating model and data validation within MLOps CI/CD pipelines.
Distinct from MLOps: Focuses on the testing/validation library aspect of MLOps rather than general operations or pipeline orchestration.
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Deepchecks is a machine learning model validation framework and MLOps testing library. It serves as an AI data quality suite and performance evaluator designed to verify the integrity and performance of models and datasets from research through production. The project functions as a model monitoring tool for tracking data drift and performance degradation in production environments. It allows for the creation of custom validation suites and utilizes a pluggable check architecture to automate quality checks within continuous integration pipelines. The framework covers a broad range of capabil
Provides a framework for automating model validation within continuous integration pipelines to ensure production readiness.