There is No Free Lunch in Data Science

During your adventures in machine learning, you may have already come across the "No Free Lunch" Theorem. Borrowing its name from the adage "there ain't no such thing as a free lunch," the mathematical folklore theorem describes the phenomena that there is no single algorithm that is best suited for all possible scenarios and data sets. There are, generally speaking, two No Free Lunch (NFL) theorems: one for machine learning and one for search and optimization. These two theorems are related and tend to be bundled into one general axiom (the folklore theorem). Although many different researchers have contributed to the collective publications on the No Free Lunch theorems, the most prevalent name associated with these works is David Wolpert.