deepchecks
An open-source solution for continuous validation of machine learning models and data, from research to production.
What is deepchecks?
Deepchecks is an open-source Python library and platform for continuous validation of machine learning models and data. It provides a comprehensive suite of tests to detect issues like data drift, performance degradation, and integrity problems across tabular, NLP, and computer vision models. The framework helps teams ensure model reliability from research through production deployment and monitoring.
Machine learning engineers, data scientists, and MLOps practitioners who need to validate, test, and monitor ML models in production environments. It's particularly valuable for teams building and deploying models at scale who require automated quality assurance.
Deepchecks offers a holistic, open-source validation solution that covers the entire ML lifecycle with specialized checks for different data types. Its unique selling point is combining testing, CI integration, and production monitoring into a single framework with extensive customization and multiple output formats for different stakeholders.
Overview
Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.
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