<aside> 📖 The bias-variance tradeoff is a key concept in machine learning that addresses the tradeoff between the two main sources of error, bias, and variance, in predictive models. This tradeoff illustrates the challenge of finding the optimal level of model complexity to achieve good generalization performance on unseen data.
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