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Hitting the Right Note - The Bias-Variance Trade-off

Hitting the Right Note - The Bias-Variance Trade-off

- [Narrator] In the last video, you understood the balancing act that goes into model simplicity and complexity. Now in this video, you are about to understand another balance. The bias variance trade off. Building predictive models is like executing the perfect skate trick, balancing between two types of errors, bias and variance. Nailing this balance is crucial for creating models that not only perform well on familiar data, but can also adapt to new or unseen data. So what is bias? Well picture trying to nail a skateboard trick, but consistently veering slightly off the one side every time that's bias. When you apply this idea to modeling, it's as if you're not fully capturing the true complexity of a skate park. Your model makes too many assumptions leading it to miss out on the full picture and not perform well across different situations. This is what causes under fitting. Now for variance. Think of attempting various skateboard tricks and landing them unpredictably in different…

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