Machine Learning
Linear regression deep dive
Assumptions, normal equations, polynomial features, regularization, when linear fails.
5 lessons
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Work through these in order—each lesson builds on the previous one.
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Lesson 1 of 5
The four OLS assumptions
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Lesson 2 of 5
Normal equations and why we don't use them
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Lesson 3 of 5
Polynomial features
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Lesson 4 of 5
Regularization effects on linear models
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Lesson 5 of 5
When linear models fail