WTF is Overfitting? When Models Memorize Not Learn #WTFisML

Your model scores perfect on training data but fails catastrophically when real customers show up.

Overfitting happens when your model memorizes training examples instead of learning patterns. It’s like cramming last year’s exam answers — then panicking when this year’s test is different. Your model becomes so specialized to training data that any variation breaks it completely.

Key Takeaways:
• Perfect training scores often mean overfitting, not success
• Models need to generalize to new data, not memorize old data
• Validation data catches overfitting before production disasters

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Видео WTF is Overfitting? When Models Memorize Not Learn #WTFisML канала EfficioLab