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AI & Machine Learning Worksheet

🤖 Eigenvalues & Eigenvectors

Chapter: AI & Machine Learning · Level ★★☆ · Time: 30 min
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After this worksheet you can
Intuit Av = lambda vDirections that only scaleWhy PCA uses themFind simple eigenvalues

🧠 Section A · Concept Check ● BEGINNER 4 × 1 = 4

1An eigenvector under A only gets:
2The scale factor is the:
3Eigen-analysis powers which ML technique?
4Eigenvalues of a diagonal matrix are:

🧮 Section B · Problem Solving ● INTERMEDIATE 2 + 3×3 = 11

5The defining equation: A v = v.
6Eigenvectors keep their under the transform.
7Eigenvalues of [[3,0],[0,7]]?
8Why does PCA pick top eigenvectors?
9Geometric meaning of lambda = 1?

🚀 Section C · Challenge ● CHALLENGE 5

10What does a negative eigenvalue do?
💭 Reflection — the most useful thing I learned:
A ___/4   B ___/11   C ___/5   Total ___/20 Teacher's Signature Parent's Signature
✂ answer key — fold or cut before handing out

1-A   2-A   3-A   4-A  |  5 lambda   6 direction   7 = 3 and 7 (diagonal)   8 = They are the directions of maximum variance in the data   9 = That direction is unchanged in length  |  10 = Flips the direction while scaling

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