Explain the bias-variance tradeoff in machine learning. How does it relate to model complexity, and what strategies can you use to find the right balance?

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The bias-variance tradeoff is a fundamental concept that explains the tension between two sources of error in machine learning models. Understanding this tradeoff is essential for building models that generalize well to new data.