Choosing the Right Metric for Evaluating Machine Learning Models

Even if data prep and feature engineering are the most time consuming parts of most data science projects, model evaluation is the easiest to f#$! up. This is a great post on the metrics you should be using to evaluate your model performance. This is an under-appreciated topic, and one where failing to understand the fundamentals can lead to significant (and costly) missteps.


Want to receive more content like this in your inbox?