By H2O.ai Team | minute read | December 26, 2013
George Box said that.
There is no best model that works for all of your data. Wolpert reiterates that as the No free lunch theorem.
Model predictive performance is domain specific. What works in one data domain has sometimes very little consequence in another one. Predictably, the rise of Domain Science: Data science needs to get closer to the business unlocking value.
Meanwhile, ensembles are here to stay!
Users want a buffet of algorithms that try to “lock-pick” the data for it’s secrets.
Time is eventually the key limiter. Data science efforts have to make best out of the budget for experimentation and use some kind of co-evolutionary technique that picks the “Champion” model of models for your data.
Robust automation and fast analytics can speedup large parts of data smithy.
Still, discovery takes patience & ingenuity.
At H2O.ai, democratizing AI isn’t just an idea. It’s a movement. And that means that it requires action. We started out as a group of like minded individuals in the open source community, collectively driven by the idea that there should be freedom around the creation and use of AI. Today we have evolved into a global company built by people from a variety of different backgrounds and skill sets, all driven to be part of something greater than ourselves. Our partnerships now extend beyond the open-source community to include business customers, academia, and non-profit organizations.