Deepchecks: Comprehensive AI & ML Model and Data Validation
Deepchecks ensures AI and ML model reliability with an open-source platform that facilitates continuous validation from development to deployment, offering extensive testing capabilities, CI & monitoring solutions.
Features
- Comprehensive Testing: Incorporate built-in and custom checks to validate Tabular, NLP, and CV datasets with Deepchecks Testing.
- CI & Testing Management: Collaborate on test results and iterate efficiently until models are production-ready with CI & Testing Management tools.
- Real-Time Monitoring: Keep track of deployed models in production with the Deepchecks Monitoring tool and get actionable insights.
Use Cases:
- From Research to Production: Seamlessly transition models from the research phase to a production environment by validating data integrity and performance.
- Collaborative Model Development: Utilize CI & Testing management for team collaboration on model enhancements and to ensure robust software engineering practices.
- Production Model Health: Monitor ongoing model performance and data health with a dynamic UI that helps detect issues quickly.
Deepchecks serves as the essential tool for teams and individuals aiming for excellence in machine learning model development and deployment, ensuring data integrity, model reliability, and operational monitoring with an open-source and collaborative approach.
Deepchecks Testing Package Alternatives:
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3. MLnative
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4. Checksum.ai
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5. Scale
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7. ML Showcase
Discover open-source machine learning projects, filter by category and explore on Github.
