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Driverless AI is H2O.ai's latest flagship product for automatic machine learning. It fully automates some of the most challenging and productive tasks in applied data science such as feature engineering, model tuning, model ensembling and production deployment. Driverless AI turns Kaggle-winning grandmaster recipes into production-ready code (Java and C++), and is specifically designed to avoid common mistakes such as under- or overfitting, data leakage or improper model validation, some of the hardest challenges in data science. Other industry-leading capabilities include automatic data visualization and machine learning interpretability.
With Driverless AI, data scientists of all proficiency levels can train and deploy modeling pipelines with just a few clicks from the GUI. Advanced users can use the client API from Python or R. Driverless AI builds hundreds or thousands of models under the hood to select the best feature engineering and modeling pipeline for every specific problem such as churn prediction, fraud detection, real-estate pricing, store sales prediction, marketing ad campaigns and many more.
With Bring-Your-Own-Recipe, domain experts and advanced data scientists can now write their own recipes and seamlessly extend Driverless AI with their favorite tools from the rich ecosystem of open-source data science and machine learning libraries.
In this talk, we explain how Driverless AI works and demonstrate it with live demos.
Arno Candel is the Chief Technology Officer at H2O.ai. He is the main committer of H2O-3 and Driverless AI and has been designing and implementing high-performance machine-learning algorithms since 2012. Previously, he spent a decade in supercomputing at ETH and SLAC and collaborated with CERN on next-generation particle accelerators.
Arno holds a PhD and Masters summa cum laude in Physics from ETH Zurich, Switzerland. He was named “2014 Big Data All-Star” by Fortune Magazine and featured by ETH GLOBE in 2015. Follow him on Twitter: @ArnoCandel.