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Why is Bias-Variance Tradeoff important in Machine Learning Fundamentals

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Answer

Understanding this tradeoff helps you choose the right model complexity, since reducing one type of error often increases the other. It is one of the core ideas behind why models overfit or underfit.
Real-world example A simple straight line model predicting house prices may miss important patterns, high bias, while a very complex model may fit every small detail of the training houses and fail on new houses, high variance.

Common follow-ups: What is overfitting, What is regularization, What is model complexity

Machine Learning Fundamentals Deep Learning Supervised & Unsupervised Learning
All 7 Bias-Variance Tradeoff questions