Fitness In Modeling

Leila Etaati notes the Scylla and Charybdis of models:

However, in the most machine learning experiences, we will face two risks :Over fitting and under fitting.
I will explain these two concepts via an example below.
imagine that we have collected information about the number of coffees that have been purchased in a café from 8am to 5pm.

Overfitting tends to be a bigger problem in my experience, but they’re both dangerous.

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