Why Cheap Learning Is In Your Future

While deep learning racks up the likes among the big data crowd, a potentially bigger phenomenon is the emergence of extremely simple machine learning models that do not require sophisticated technical and mathematical skills, or what machine learning expert Ted Dunning calls "cheesy and cheap machine learning," or simply "cheap learning." "Deep learning is all the rage, all the fashion, and of course everybody has to like it because of that, because we're all so fashionable in the tech industry," Dunning, who is MapR Technologies' chief application architect, tells Datanami in a recent interview. "But what also is happening is cheap learning, which are very simple models to solve very simple problems, but which in aggregate give a very large value." In the new cheap learning age, developers will avail themselves to the powerful and easy to use machine learning frameworks -- and do so without having to understand all the complex mathematics driving the predictions and recommendations and optimizations under the covers, Dunning says. "They can use machine learning without even realizing it's machine learning, and without having to become mathematical sophisticates," says says Dunning, who co-authored with Ellen Friedman two machine learning books, including "Practical Machine Learning: Innovations in Recommendation" and "Practical Machine Learning: A New Look at Anomaly Detection."