Traps, pitfalls and misconceptions of machine learning applied to scientific disciplines

This has corresponded to an understandable hype especially for the remarkable results achieved in some cases. Therefore, practitioners of Scientific Disciplines have become interested in utilizing new Machine Learning techniques, and have sometimes started doing so with mixed success.

The purpose of this paper is to describe some of the common Traps, Pitfalls and Misconceptions of Machine Learning as relevant to the Scientific Discipline, and how to avoid them. In fact, Machine Learning and Deep Learning are fast evolving fields, and some of the astonishing results achieved recently sit on small but important details which have become the state of the art. Some of these details are not broadly known by the scientific community.