.. sampledoc documentation master file, created by sphinx-quickstart on Mon Apr 25 15:24:53 2016. You can adapt this file completely to your liking, but it should at least contain the root `toctree` directive. .. _overview: ======== Overview ======== H2O Driverless AI is an artificial intelligence (AI) platform for automatic machine learning. Driverless AI automates some of the most difficult data science and machine learning workflows, such as feature engineering, model validation, model tuning, model selection, and model deployment. It aims to achieve the highest predictive accuracy, comparable to expert data scientists, but in a much shorter time thanks to end-to-end automation. Driverless AI also offers automatic visualization and machine learning interpretability (MLI). Especially in regulated industries, model transparency and explanation are just as important as predictive performance. Modeling pipelines (feature engineering and models) are exported (in full fidelity, without approximations) both as Python modules and as Java standalone scoring artifacts. Apart from the standard :ref:`experiment workflow ` for model building, DAI offers an :ref:`experiment setup wizard ` that makes it simple for you to set up a Driverless AI experiment and ensure that the experiment's settings are optimally configured for your specific use case. Driverless AI runs on commodity hardware. It was also specifically designed to take advantage of graphics processing units (GPUs), including multi-GPU workstations and servers such as the `NVIDIA DGX-1 `__ for orders of magnitude faster training. This document describes how to install and use Driverless AI. For more information about Driverless AI, see https://www.h2o.ai/products/h2o-driverless-ai/. For a third-party review, see https://www.infoworld.com/article/3236048/machine-learning/review-h2oai-automates-machine-learning.html. **Have Questions?** If you have questions about using Driverless AI, post them on Stack Overflow using the driverless-ai tag at http://stackoverflow.com/questions/tagged/driverless-ai. You can also post questions on the `H2O.ai Community Slack workspace `__ in the **#driverlessai** channel. If you have not signed up for the H2O.ai Community Slack workspace, you can do so here: https://www.h2o.ai/community/. .. toctree:: :maxdepth: 2 :caption: Release Notes release_notes blog .. toctree:: :maxdepth: 2 :caption: Introduction introduction .. toctree:: :maxdepth: 2 :caption: Licensing and Version Support licenses .. toctree:: :maxdepth: 2 :caption: Installation and Upgrade installation .. toctree:: :maxdepth: 2 :caption: Configuration configuration .. toctree:: :maxdepth: 2 :caption: Datasets datasets .. toctree:: :maxdepth: 2 :caption: Data Insights autoviz .. toctree:: :maxdepth: 2 :caption: Custom Recipes custom_recipes individual-recipe .. toctree:: :maxdepth: 2 :caption: Feature Engineering feature-engineering feature-count .. toctree:: :maxdepth: 2 :caption: Modeling modeling dai-wizard autodoc .. toctree:: :maxdepth: 2 :caption: Machine Learning Interpretability mli .. toctree:: :maxdepth: 2 :caption: Generative AI dai-h2ogpt .. toctree:: :maxdepth: 2 :caption: Scoring on New Datasets score-on-another-dataset .. toctree:: :maxdepth: 2 :caption: Transforming Datasets transform-another-dataset .. toctree:: :maxdepth: 2 :caption: Scoring Pipelines scoring_pipelines .. toctree:: :maxdepth: 2 :caption: Productionization deployment .. toctree:: :maxdepth: 2 :caption: Clients clients .. toctree:: :maxdepth: 2 :caption: Monitoring and Logging monitoring_and_logging .. toctree:: :maxdepth: 2 :caption: Security security_main .. toctree:: :maxdepth: 2 :caption: Frequently Asked Questions faq .. toctree:: :maxdepth: 2 :caption: Appendices third-party-integrations .. toctree:: :maxdepth: 2 :caption: References references .. only:: html .. toctree:: :maxdepth: 1 :caption: Third-Party Notices docs-licenses/licenses .. toctree:: :maxdepth: 2 :caption: Translations Go to User Guide in Chinese Go to User Guide in Korean