BitWithBite
AI & Machine Learning Worksheet
🤖 Vector Operations
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NameClassDate
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Add and scale vectorsDot productNorms (length)Cosine similarity idea🧠 Section A · Concept Check ● BEGINNER 4 × 1 = 4
1[1,2] + [3,4] =:
2Dot product of [1,2] and [3,4]:
3The L2 norm of [3,4] is:
4Dot product of perpendicular vectors is:
🧮 Section B · Problem Solving ● INTERMEDIATE 2 + 3×3 = 11
52 * [1,3] = [2, ].
6Dot product multiplies pairwise then .
7Compute [2,1].[4,3].
8Norm of [6,8]?
9Why does ML use dot products constantly?
🚀 Section C · Challenge ● CHALLENGE 5
10Two docs as vectors - how tell similarity?
💭 Reflection — the most useful thing I learned:
A ___/4 B ___/11 C ___/5 Total ___/20
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✂ answer key — fold or cut before handing out
1-A 2-A 3-A 4-A | 5 6 6 sums/adds 7 = 2*4 + 1*3 = 11 8 = sqrt(36+64) = 10 9 = Neuron outputs, similarities, projections are all dot products | 10 = Cosine similarity of their embedding vectors