Overfitting vs Underfitting - Explained
IIn this video, we’ll break down two of the most important concepts in machine learning: overfitting and underfitting. Using a visual example with polynomial curve fitting, we’ll explore how models can be too simple or too complex, and how to find the right balance for better generalization. Plus, learn about key techniques like regularization, early stopping, and dropout to prevent overfitting in modern deep learning.
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Contents
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00:00 - Intro
00:52 - Underfitting
01:27 - Overfitting
02:15 - Balanced fitting
02:37 - Regularization
03:17 - Summary
03:56 - Outro
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