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Test your understanding with targeted questions related to the topic.
Question 1
Easy
Define best approximation in your own words.
💡 Hint: Think about it as finding the nearest point.
Question 2
Easy
What does the error vector signify?
💡 Hint: Look for a relationship between the original and approximated values.
Practice 4 more questions and get performance evaluation
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What is the best way to define best approximation?
💡 Hint: Refer back to the definition discussed in class.
Question 2
The error vector is known for being orthogonal to what?
💡 Hint: Remember the definition of the Projection Theorem.
Solve 2 more questions and get performance evaluation
Push your limits with challenges.
Question 1
Given a vector v = (4, 3) and a subspace defined by w1 = (1, 1) and w2 = (1, -1), find the best approximation vector v_b.
💡 Hint: Break down the steps using projection formulas.
Question 2
In a practical setting, if you have a data set with noise and want to fit your model optimally using least squares, how would you identify the best parameters?
💡 Hint: Utilize derivatives to find minima in your functions.
Challenge and get performance evaluation