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Tuesday, October 20 • 13:30 - 14:00
What If We Could Use Machine Learning Models as Tables?

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In most machine learning tasks, one has to first organize data in some form and then turn it into information about the problem that needs to be solved. One could say that the requirement to train many machine learning algorithms is information, not just data. Given that most of the world's structured and semi-structured data (information) lives in databases, it makes sense to bring ML capabilities straight to the databases themselves. In this talk we want to present to the Percona community what we have learned in the effort of enabling existing databases like MariaDB and Postgres with frictionless ML powers.

avatar for Jorge Torres

Jorge Torres

CEO, MindsDB
Jorge Torres is the Co-founder & CEO of MindsDB. He is also a visiting scholar at UC Berkeley researching machine learning automation and explainability. Before founding MindsDB, he worked for a number of data-intensive start-ups, most recently working with Aneesh Chopra (the first... Read More →

avatar for Alick Smith

Alick Smith

Manager, Professional Services, Percona

Tuesday October 20, 2020 13:30 - 14:00 EDT