In his Top 10 Data Science Mistakes, John Elder shares lessons learned from 20 years of data science consulting experience. Avoiding these mistakes are cornerstones to any successful analytics project.
In this paper about Mistake #1 you will learn about the dangers of, and how to avoid, overfit where training cases focus the model too much on the peculiarities of that data to the detriment of inducing general lessons that will apply to similar, but unseen, data.