Wat we doen

We’re excited to bring you the latest happenings in AI, Machine Learning, Deep Learning, Data Science and Big Data.

Who are we? We’re H2O.ai ( https://www.h2o.ai/ ), creators of the world’s leading open-source machine learning platform, used by hundreds of thousands of data scientists and 18,000 organizations around the world.

Our goal is to congregate with data enthusiasts and discuss trending topics in the world of AI. We also regularly invite esteemed industry influencers and thought leaders who talk shop on all things data science.

Sound like a good time?

Interested in H2O or our automatic machine learning platform, H2O Driverless AI? Learn more here: https://www.h2o.ai/download/

Already a rainmaker (H2O power user) or have questions? Please visit our StackOverflow page. ( http://stackoverflow.com/questions/tagged/h2o )

If you’d like to speak at future meetups, co-promote your meetup or inquire about sponsorship opportunities, please reach out to ian@h2o.ai.

Read about our code of conduct here: https://www.h2o.ai/code-of-conduct/

Thank you for advancing the future of data science,

Ian

Follow us on Twitter: @h2oai

Geplande evenementen (1)

Building Recipes for Anti-Money Laundering Usecases

***** PLEASE NOTE: Please grab your free spot here: https://www.eventbrite.com/e/building-recipes-for-anti-money-laundering-usecases-tickets-73012072073 Your RSVP on meetup will not count towards your spot****** This is a joint meetup in collaboration with Data Riders Group: https://www.meetup.com/datariders Hello Makers! Join us this evening as we discuss machine learning recipes for anti-money laundering use-cases. Following is a brief agenda for the evening: 6:00 - 6:30 PM: Doors open for networking and pizza 6:30 - 7:15 PM: Ashrith's talk 7:15 - 7:30 PM: Q&A ------------------------------------------------------------------------------------------------------ Description: How do you solve Anti-Money Laundering using Driverless AI? In this presentation, we will see how to reduce false-positive alerts, which is a big problem for financial institutions. Using this approach you can quickly and easily design models that will reduce false-positive alerts significantly while keeping the false-negative number low. Ashrith's Bio: Ashrith is the security scientist designing anomalous detection algorithms at H2O.ai. He recently graduated from the Center of Education and Research in Information Assurance and Security (CERIAS) at Purdue University with a Ph.D. in Information security. He is specialized in anomaly detection on networks under the guidance of Dr. William S. Cleveland. He tries to break into anything that has an operating system, sometimes into things that don’t. He has been christened as “The Only Human Network Packet Sniffer” by his advisors. When he is not working he swims and bikes long distances.

Vorige evenementen (140)

Webinar: What's New in H2O Driverless AI

Live Webinar