Evaluating Models

Evaluating machine learning models is like checking to see if a recipe turned out the way you wanted. Imagine you are baking cookies and want them to be my favorite type, soft and chewy! After baking, you take a bite to see if they are just right. If they’re too hard or soft, you know something went wrong. In the same way, when we build a machine learning model, we need to test it to ensure it is doing what we want. This testing, or evaluation, helps us determine if the model is making accurate predictions or if we need to adjust the “ingredients” to get better results.