Memorizing ≠ Learning! The Truth About Overfitting!

Описание: Ever studied so hard that you memorized every answer… but failed when the questions changed?
That’s overfitting — one of the most common problems in Machine Learning.

Overfitting happens when your model learns the training data too well — including all the noise and errors.
It performs perfectly on the old data but fails miserably on new data.

In this video, you’ll learn:
✅ What overfitting really means
✅ Why it hurts your model’s performance
✅ How to fix it using cross-validation, regularization, and better data

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