Perfection is achieved only by making mistakes. The same holds true when you work with machine learning algorithms to build models. Most of the time, it is not obvious how to proceed and navigate at the beginning, and professionals are bound to make mistakes, especially those who are novices in the domain. Here is a list of the most common mistakes that are committed while working with machine learning algorithms. Hopefully, you will learn and draw valuable insights from this article that you could apply to your work.