Have you ever spoken with a data scientist who said: When I see an accuracy of 80% or higher, I know something might be wrong. I bet your first reaction is confusion because the above statement defies any logic, at least theoretically. It is normal to ask: Why? Is not a higher accuracy better? Theoretically, YES! In practice, higher accuracy may not be better. Most data science courses promote high accuracy or show statistics that translate to 100% accuracy or are equally r

Research is, in my opinion, another very important step in the project lifecycle. I read articles claiming that Data Science is dead because most of the work can be automated. However research can never be automated and because of it, I believe that data science shall live on. I make this claim with great awareness about how businesses are evolving and how the industry is educating itself on data richness and machine learning. Research is about searching for something. Acco