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Welcome to Deepchecks!#

Deepchecks is the leading tool for testing, validating and monitoring your machine learning models and data, and it enables doing so with minimal effort. Deepchecks accompanies you through various validation and testing needs such as verifying your data’s integrity, inspecting its distributions, validating data splits, evaluating your model and comparing between different models.

Deepchecks Suite of Checks

Start Working with Deepchecks Testing#

🏃‍♀️ Tabular Quickstarts 🏃‍♀️

End-to-end guides to start testing your tabular data & model in 5 minutes.

💁‍♂️ Get Help & Give Us Feedback 💁

Links for how to interact with us via our Slack Community or by opening an issue on Github.

🤓 User Guide 🤓

A comprehensive view of deepchecks concepts, customizations, and core use cases.

💻 Install 💻

Full installation guide (quick one can be found in quickstarts)

🚀 Interactive Demo of the Tabular Checks 🚀

Play with some of the existing tabular checks and see how they work on various datasets with custom corruptions injected.

🤖 API Reference 🤖

Reference and links to source code for Deepchecks’ components

🏃‍♀️ Vision Quickstarts (Note: CV is in Beta Release) 🏃‍♀️

End-to-end guides demonstrating how to start working with various CV use cases (object detection, classification and more)

🔤️ NLP Quickstarts (Note: NLP is in Alpha Release) 🔤️

Initial release demonstrating how to test NLP models and data. Future releases to come! Currently supports text classification and token classification.

Get Help & Give Us Feedback#

Join Our Community 👋

In addition to perusing the documentation, feel free to:

To support us, please give us a star ⭐️ on Github, it really means a lot for open source projects!

Deepchecks’ Components#

Continuous validation of ML models and data includes testing throughout the model’s lifecycle:

Phases for Continuous Validation of ML Models and Data

Head over to the relevant documentation for more info:

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Testing Package (Here)

Tests during research and model development

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Testing Package CI/CD Usage

Tests before deploying the model to production

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Monitoring

Tests and continuous monitoring during production