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H2O.ai brings AutoML to Equifax Ignite with Driverless AI

H2O.ai, the open source leader in artificial intelligence (AI) and machine learning (ML), today announced the availability of H2O AutoML and Driverless AI within Equifax Ignite®.

H2O is a leading open-source AI platform, and its Driverless AI is a leading automatic machine learning (AutoML) platform that will enable users of Equifax Ignite to easily build and deploy machine learning models. H2O Driverless AI automates time-consuming machine learning workflows with automatic feature engineering, model tuning, and model selection to achieve the highest predictive accuracy within the shortest amount of time. Equifax Ignite allows users to create analytical insights via end-to-end Equifax solutions or through modular microservices that support their existing technology platforms and workflows.

“For years, our customers in financial services, retail and healthcare have been leveraging Equifax differentiated data with H2O machine learning, and it was only a matter of time before we integrated best-in-class H2O AutoML and Driverless AI into the Equifax environment,” said Sri Ambati, CEO of H2O.ai. “The Equifax Ignite customer community can now leverage these industry leading solutions to make better predictions and better adapt in today’s fast-changing business climate.”

H2O is a fully open-source, distributed in-memory machine learning platform with linear scalability. It supports the most widely used statistical and machine learning algorithms including gradient boosted machines, generalized linear models, deep learning and more.

“Over the years, our data science experts have harnessed the power of artificial intelligence for insightful and transparent client experiences,” said Prasanna Dhore, Chief Data & Analytics Officer at Equifax. “Helping businesses apply machine learning with technical sophistication and ease is a goal we share with H2O.ai, and we’re excited to make their Driverless AI available to our Ignite community.”

H2O Driverless AI can ingest data from a variety of data sets and can be deployed everywhere, including all cloud and on-premise environments.