Guest Opinion: Time to go Deep on Deep Learning

A core difference between Machine Learning and Deep Learning is in the feature selection process, which is the function by which data is chosen in creating a predictive model. In Machine Learning, domain expertise is required to code the inputs used to build a model. For example, let's say you are building a model for facial recognition. You might start by determining where the eyes, nose and mouth are located. Doing this is something we humans can do very easily; however, for a machine, it's not so simple.