Towards Human-Centered Machine Learning

H2O.ai is the leader in AI with its visionary open source platform, H2O. Its mission is to democratize AI for all. More than 18,000 companies use open-source H2O in mission-critical use cases for Finance, Insurance, Healthcare, Retail, Telco, Sales, and Marketing. H2O.ai recently launched Driverless AI that uses AI to do AI in order to provide an easier, faster and cheaper means of implementing data science.

H2O.ai

Join us this evening to discuss interpretable machine learning and the techniques that go behind making a white-box models.

Plexpod Westport Commons

Hello KC Data Scientists!Please join us this evening, October 29th, to discuss interpretable machine learning and the techniques that go behind making a white-box model! Following is a brief agenda for the evening:6:00 - 6:30 PM: Doors open for networking and pizza6:30 - 7:15 PM: Talk on Machine Learning Interpretability7:15 - 7:30 PM: Q&amp;A7:30 - 8:00 PM: NetworkingDescription:Machine learning systems are used today to make life-altering decisions about employment, bail, parole, and lending. Moreover, the scope of decisions delegated to machine learning systems seems likely only to expand in the future. Unfortunately, serious discrimination, privacy, and even accuracy concerns can be raised about these systems. Many researchers and practitioners are tackling disparate impact, inaccuracy, privacy violations, and security vulnerabilities with a number of brilliant, but often siloed, approaches. This presentation illustrates how to combine innovations from several sub-disciplines of machine learning research to train explainable, fair, trustable, and accurate predictive modeling systems. Together these techniques can create a new and truly human-centered type of machine learning suitable for use in business- and life-critical decision support.Speakers:Bahador KhaleghiBahador’s unique technical background, which he has gained over the last thirteen years, is quite diverse entailing a wide range of disciplines including machine learning, statistical information fusion, and signal processing. He obtained his PhD from CPAMI at the University of Waterloo. Over the last seven years, he has actively contributed to industrial R&amp;D projects in various domains including Telematics, mobile health, predictive maintenance, and customer analytics. In his last role, Bahador acted as the technical lead of the explainability team at Element AI and was focused on developing and applying methodologies that enhance transparency, trustability, and accessibility of AI solutions.Keith WeiszKeith is a Machine Learning Evangelist and a Data Strategist at H2O.ai, based in Kansas City. His expertise is helping organizations align their business goals with their data strategy. Taking into account people, process and technology, he helps enterprises leverage their data assets to gain market share, improve profits and/or reduce risk.

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Towards Human-Centered Machine Learning

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Towards Human-Centered Machine Learning

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