.. image:: /_static/images/welcome/deepchecks_continuous_validation_light.png :alt: Deepchecks Continuous Validation: Testing, CI & Monitoring :align: center :width: 80% .. _welcome_depchecks_testing: ======================== Welcome to Deepchecks! ======================== `Deepchecks `__ is a holistic open-source solution for all of your AI & ML validation needs, enabling you to thoroughly test your data and models from research to production. We invite you to: - See the following :ref:`Deepchecks Components ` section for more info about the Testing, CI, & Monitoring components and for links to their corresponding documentation. - Go to the :ref:`welcome__start_with_deepchecks_monitoring` section to have it up and running quickly and see it in action. .. .. image:: /_static/images/general/checks-and-conditions.png .. :alt: Deepchecks Testing Suite of Checks .. :width: 65% .. :align: center .. image:: /_static/images/general/model-evaluation-suite.gif :alt: Deepchecks Suite Run :width: 65% :align: center .. _welcome__deepchecks_components: Deepchecks' Components for Continuous Validation ================================================== Deepchecks provides comprehensive support for your testing requirements, from examining data integrity and assessing distributions, to validating data splits, comparing models and evaluating their performance across the model's entire development process. .. grid:: 1 :gutter: 1 1 3 3 .. grid-item-card:: Testing Docs (here) :link-type: ref :link: welcome__start_with_deepchecks_testing :img-top: /_static/images/welcome/testing_tile.png :columns: 6 4 4 4 Tests during research and model development .. grid-item-card:: CI Docs :link-type: ref :link: using_deepchecks_ci_cd :img-top: /_static/images/welcome/ci_tile.png :columns: 6 4 4 4 Tests before deploying the model to production .. grid-item-card:: Monitoring Docs :link-type: ref :link: deepchecks-mon:welcome__start_with_deepchecks_monitoring :img-top: /_static/images/welcome/monitoring_tile.png :columns: 6 4 4 4 Tests and continuous monitoring during production Deechecks' continuous validation approach is based on testing the ML models and data throughout their lifecycle using the exact same checks, enabling a simple, elaborate and seamless experience for configuring and consuming the results. Each phase has its relevant interfaces (e.g. visual outputs, python/json output results, alert configuration, push notifications, RCA, etc.) for interacting with the test results. .. image:: /_static/images/welcome/testing_phases_in_pipeline_with_tiles.png :alt: Phases for Continuous Validation of ML Models and Data :align: center | .. _welcome__start_with_deepchecks_testing: Get Started with Deepchecks Testing ======================================== .. grid:: 1 :gutter: 3 .. grid-item-card:: 🏃‍♀️ Quickstarts 🏃‍♀️ :link-type: ref :link: welcome__quickstarts Downloadable end-to-end guides, demonstrating how to start testing your data & model in just a few minutes. .. grid-item-card:: 💁‍♂️ Get Help & Give Us Feedback 💁 :link-type: ref :link: welcome__get_help Links for how to interact with us via our `Slack Community `__ or by opening `an issue on Github `__. .. grid-item-card:: 💻 Install 💻 :link-type: doc :link: /getting-started/installation Full installation guide (quick one can be found in quickstarts) .. grid-item-card:: 🤓 General: Concepts & Guides 🤓 :link-type: ref :link: general__index A comprehensive view of deepchecks concepts, customizations, and core use cases. .. grid-item-card:: 🔢 Tabular 🔢 :link-type: ref :link: tabular__index Quickstarts, main concepts, checks gallery and end-to-end guides demonstrating how to start working Deepchecks with tabular data and models. .. grid-item-card:: 🔤️ NLP 🔤️ :link-type: ref :link: nlp__index Quickstarts, main concepts, checks gallery and end-to-end guides demonstrating how to start working Deepchecks with textual data. Future releases to come! .. grid-item-card:: 🎦‍ Computer Vision (Note: in Beta Release) 🎦‍ :link-type: ref :link: vision__index Quickstarts, main concepts, checks gallery and end-to-end guides demonstrating how to start working Deepchecks with CV data and models. Built-in support for PyTorch, TensorFlow, and custom frameworks. .. grid-item-card:: 🚀 Interactive Checks Demo 🚀 :link-type: url :link: https://checks-demo.deepchecks.com/?check=No+check+selected &utm_source=docs.deepchecks.com&utm_medium=referral& utm_campaign=welcome_page&utm_content=checks_demo_card Play with some of the existing tabular checks and see how they work on various datasets with custom corruptions injected. .. grid-item-card:: 🤖 API Reference 🤖 :link-type: doc :link: /api/index Reference and links to source code for Deepchecks Testing's components. .. _welcome__quickstarts: 🏃‍♀️ Testing Quickstarts 🏃‍♀️ ============================== .. grid:: 1 :gutter: 3 .. grid-item-card:: 🔢 Tabular 🔢 :link-type: doc :link: /tabular/auto_tutorials/quickstarts/index :columns: 4 .. grid-item-card:: 🔤️ NLP 🔤️ :link-type: doc :link: /nlp/auto_tutorials/quickstarts/plot_text_classification :columns: 4 .. grid-item-card:: 🎦‍ Vision 🎦‍ (in Beta) :link-type: doc :link: /vision/auto_tutorials/quickstarts/index :columns: 4 .. _welcome__get_help: Get Help & Give Us Feedback ============================ .. admonition:: Join Our Community 👋 :class: tip In addition to perusing the documentation, feel free to: - Ask questions on the `Slack Community `__. - Post an issue or start a discussion on `Github Issues `__. - To contribute to the package, check out the `Contribution Guidelines `__ and join the `contributors-q-&-a channel `__ on Slack, or communicate with us via github issues. To support us, please give us a star on ⭐️ `Github `__ ⭐️, it really means a lot for open source projects!