Lecture
Overfitting vs Underfitting
Description
This lecture discusses common mistakes in machine learning, focusing on overfitting and underfitting. It explains how model complexity affects error rates, using polynomial functions as examples. The instructor demonstrates how to find the optimal complexity for a model and provides solutions for handling overfitting.
Official source
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