Deep learning made easier with transfer learning

Deep learning has provided extraordinary advances in problem spaces that are poorly solved by other approaches. This success is due to several key departures from traditional machine learning that allow it to excel when applied to unstructured data. Today, deep learning models can play games, detect cancer, talk to humans, and drive cars. But the differences that make deep learning powerful also make it costly. You may have heard that deep learning success requires massive data, expensive hardware, and even more expensive elite engineering talent.