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Understanding the Bias-Variance Tradeoff Like a Pro
- Bias is the error from incorrect assumptions in the learning algorithm.
- High bias means the model is too simple, while low bias means the model captures the data patterns accurately.
- The bias-variance tradeoff aims to minimize total error by balancing low bias and low variance.
- Understanding this tradeoff helps in debugging models faster and making better decisions as an AI engineer.
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