Module 1 Review & Cheat Sheet
1. Key Takeaways
- Data Representation:
- Scalar (0D): Magnitude only.
- Vector (1D): Magnitude + Direction.
- Matrix (2D): Grid / Transformation.
- Tensor (ND): Generalization to N dimensions.
- Operations:
- Addition: Head-to-Tail geometric interpretation.
- Dot Product: Measures Similarity (Projection).
- Matrix Multiply: Applies a Linear Transformation.
- Systems of Equations:
- Geometric interpretation: Intersection of lines/planes.
- Gaussian Elimination: Algorithm to solve Ax = b.
2. Cheat Sheet
| Term | Notation | Formula / Definition | Code (NumPy) |
|---|---|---|---|
| Dot Product | a ċ b | ∑ aibi = ||a|| ||b|| cos θ | np.dot(a, b) |
| Matrix Mult | AB | Row ċ Column | np.matmul(A, B) or A @ B |
| L2 Norm | ||x|| | √(∑ xi2) | np.linalg.norm(x) |
| Cosine Sim | cos θ | (a ċ b) / (||a|| ||b||) | Manual |
| Transpose | AT | Swap Rows/Cols | A.T |
3. Interactive Flashcards
Test your knowledge. Click a card to flip it.
Question 1
Answer 1
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