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Check your knowledge

1.

Why is linear regression a popular model?

It's fast to calculate and easily interpreted

It's easy to extrapolate from and the fitting procedure doesn't require ‘tuning’ to find an optimum solution

Both options are correct

2.

What is the difference between multiple and simple regression?

Simple regression uses special mathematics to speed up analysis

Multiple regression predicts multiple labels, but simple regression doesn't

Multiple regression accepts multiple features, but simple regression doesn't

3.

What are the main strengths and weaknesses of polynomial regression, compared to simple linear regression?

Polynomial regression is a more popular method than linear regression, but it always needs to be fitted iteratively

Polynomial regression can explain nonlinear relationships, but it often makes extreme predictions when extrapolated

Polynomial regression can be extrapolated, unlike simple linear regression, but it can take a long time to compute

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