How Expert Data Science Teams Use AutoML to Increase Scalability and Efficiency

Presented by

Travis Couture, Solutions Engineer at H2O.ai

About this talk

AutoML is helping lower the barrier to entry and accelerate the time it takes to build and deploy machine learning models. H2O's Driverless AI and Open Source library both feature AutoML capabilities that range from hyperparameter selection to advanced feature engineering and model ensembling. However, it is important to note that AutoML is not intended to replace expert data science teams but can instead be used by such teams to augment their scalability and efficiency while still allowing them to maintain control over the end to end machine learning lifecycle. In this webinar, you will learn: - Evolution of AutoML - How expert data science teams can leverage AutoML - How H2O Driverless AI allows expert Data Science teams to maintain control when using AutoML Presenter: Travis Couture, Solutions Engineer at H2O.ai

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H2O.ai is the maker of H2O, the world's best machine learning platform and Driverless AI, which automates machine learning. H2O is used by over 200,000 data scientists and more than 18,000 organizations globally. H2O Driverless AI does auto feature engineering and can achieve 40x speed-ups on GPUs.