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AI Interview Core Questions
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Module 1
Linear Algebra for AI Interviews
1
Matrix Operations: Multiplication and 2x2 Determinants
Perform basic matrix operations by hand (multiplication, 2x2 determinant).
2
Matrix Rank and Linear Independence
Explain the concept of matrix rank in terms of linear independence.
Understanding Eigenvalues and Eigenvectors
Define eigenvalues and eigenvectors with the equation Av = λv.
4
Eigenvalues and Eigenvectors of 2x2 Matrices
Compute the eigenvalues and eigenvectors for a simple 2x2 matrix.
5
Eigenvalues & Eigenvectors: Scaling & Invariant Directions
Explain the geometric interpretation of eigenvalues and eigenvectors as scaling and invariant directions.
6
Components of SVD: A = UΣVᵀ
Describe the components of Singular Value Decomposition (SVD): A = UΣVᵀ.
7
SVD for Dimensionality Reduction: Truncation Explained
Explain how SVD is used for dimensionality reduction through truncation.
8
SVD in Image Compression and Recommender Systems
Provide a real-world example of SVD, such as in image compression or recommender systems.
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