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Aug 15 (edited) • General Discussion 💬
📒 AI Terms Daily Dose: Overfitting
Term: Overfitting
Day: 6
Level: Fluency
Category: Learning & Models
🪄 Simple Definition:
When an AI model learns training data so well that it fails to work accurately on new, unseen data.
🌟 Expanded Definition:
Overfitting occurs when a model memorizes patterns, details, and even noise from the training data instead of learning generalizable rules. This leads to high accuracy on the training set but poor performance in real-world applications where the data is different.
⚡ In Action:
A real estate price prediction model perfectly fits last year’s housing data but gives wildly inaccurate estimates for this year because the market has shifted.
💡 AIS+ Pro Tip:
Combat overfitting with techniques like regularization, dropout, using more diverse data, or validating on unseen datasets. Keep an eye on the gap between training and validation accuracy during model development.
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📒 AI Terms Daily Dose: Overfitting
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