Supervised Learning Use Cases: Low-Hanging Fruit in Data Science for Businesses

In the past few years, machine learning (ML) has revolutionized the way we do business. A disruptive breakthrough that differentiates machine learning from other approaches to automation is a step away from the rules-based programming. ML algorithms allowed engineers to leverage data without explicitly programming machines to follow specific paths of problem-solving. Instead, machines themselves arrive at the right answers based on the data they have. This capability made business executives reconsider the ways they use data to make decisions. In layman terms, machine learning is applied to make forecasts on incoming data using historic data as a training example.