Model Evaluation, Model Selection, and Algorithm Selection in Machine Learning
Sebastian Raschka. 2018. (View Paper → )
The correct use of model evaluation, model selection, and algorithm selection techniques is vital in academic machine learning research as well as in many industrial settings. This article reviews different techniques that can be used for each of these three subtasks and discusses the main advantages and disadvantages of each technique with references to theoretical and empirical studies
Having a basic understanding of Machine Learning is becoming more important for Product Managers. This 50 page paper might seem like a big investment - but it’s a genuine alternative to reading a bunch of textbooks on the subject. There’s minimal math notation and the author does a relatively good job of keeping language accessible.