The stakes in managing model risk are at an all-time high, but luckily automated machine learning provides an effective way to reduce these risks. Learn more.
Part 2 in a series on the emerging practice of "green AI." In this blog, the focus is on actionable ways AI practitioners can build their models to minimize the cost of Red AI.
Find out how to approach machine learning projects in a sustainable and cost-efficient manner by reassessing the efficiency metrics applies to models.
Another year at HIMSS has come and gone and DataRobot remains as energized as ever! Learn how DataRobot AI Platform can help the healthcare industry.
According to Gartner, 51% of enterprises have started their AI journey, but just 10% of ML solutions get deployed. Learn why in the article.
With DataRobot, we can modernize our approach of forecasting solar irradiance, use these models to optimize solar power generation, and contribute to the clean energy revolution across the globe.
Genetic or evolutionary algorithms mimic natural selection, by eliminating weaker solutions to a given problem and allowing the stronger ones to be developed into future generations of possible solutions. Eureqa uses this approach to mimic the scientific process.
AI impact assessments are more than black and white compliance documents. Read more about AI Impact Statements - empathy, imperfection, and responsibility.
We met with Randy Singh, Director of Strategy and Sporting at McLaren Racing, to see how they look at data and identify what matters most.