Evaluating Data Science Projects: A Case Study Critique


I've written two blog posts on evaluation--the broccoli of machine learning. Both types are important not only to data scientists but also to managers and executives, who must evaluate project proposals and results. To managers I would say: It's not necessary to understand the inner workings of a machine learning project, but you should understand whether the right things have been measured and whether the results are suited to the business problem. You need to know whether to believe what data scientists are telling you. To this end, here I'll evaluate a machine learning project report.