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Data Science Academy · Lesson

How PCA Finds Components

Variance directions, intuitively.

Variance Is Information

PCA starts from one idea: the directions where your data spreads most carry the most information. That spread is called variance.

Find the Biggest Spread

PCA hunts for the single axis along which points vary the most. That direction becomes the first principal component.

All lessons in this course

  1. The Curse of Too Many Features
  2. How PCA Finds Components
  3. Scale First, Then Fit PCA
  4. Choose Components With Scree Plots
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