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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What does SVD stand for?
💡 Hint: Think about the components it factors into.
Question 2
Easy
What is the type of matrix that contains the singular values in SVD?
💡 Hint: This matrix has non-zero entries only along the diagonal.
Practice 4 more questions and get performance evaluation
Interactive Quizzes
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What is the formula for Singular Value Decomposition?
- A = ABC
- A = UΣV^T
- A = UVΣ
💡 Hint: Recall the notation of SVD.
Question 2
Is the matrix Σ in SVD a diagonal matrix?
- True
- False
💡 Hint: What kind of entries does a diagonal matrix have?
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Consider a matrix A. Derive its SVD step-by-step, explaining each step's significance.
💡 Hint: Visualize each step as layers building up the understanding of the matrix's structure.
Question 2
Provide a real-world dataset and perform PCA using SVD to reduce dimensions. Explain the retained singular values' significance.
💡 Hint: Think about how the information is expressed dimensionally in the context of real-world applications.
Challenge and get performance evaluation