What we're about

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

Upcoming events (1)

How to Detect Fraud Quicker with AI

Online event

Electronic Fraud is prevalent in almost every walk of life these days. The directions in which society is moving forward, monetary instruments are only going to get more digital, and transactions are only going to get more electronic. In this almost-exponential growth fraudsters have a leg up. This is because legacy systems that are fighting are old, and have not accounted for newer fraudulent behaviors. While the new systems with ML models could be accurate but slow. For one to catch fraud in an acceptable time, the systems have to be fast and quickly modifiable to changing fraudulent methods. In this talk, we speak about different methods which can make your AI systems faster, and valuable toward identifying fraud. These systems also maintain a high level of accuracy. Some of these methods that we would discuss are: - Different ways of implementing the models - Variations in hyper-parameters of models - Highly accurate features that are valuable that are modifiable At the end of this webinar you would be able to understand how to: - Build better features for fraud - How to build models and model implementations to speed up the decision

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