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IIT M DIPLOMA AN EXAM QDD4 01 Dec 2024 - 01 Dec 2024

MLF Quiz 215 questions40 marks12 MCQ · 3 MSQDiploma / afternoon / QDD4
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Q1MSQ3 marksselect all that apply
Note: BH is a conjugate transpose of B. question figure
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Q2MSQ3 marksselect all that apply
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Q3MCQ3 marks
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Q5MCQ3 marks
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Q6MCQ3 marks
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Q7MCQ3 marks
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  1. (3,7)
  2. (0.4, 1.8)
  3. (0,0)
  4. (-1,0)
Comprehension passage - the questions below it refer to this
Based on the above data answer the given subquestions. question figure
Q8MCQ2 marks
Which of the following options is/are true?
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Q9MCQ2 marks
Which of the following options is/are true ?
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Q10MCQ2 marks
Which of the following options is true?
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Comprehension passage - the questions below it refer to this
Based on the above data answer the given subquestions. question figure
Q11MCQ3 marks
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Q12MCQ3 marks
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Q13MCQ3 marks
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Q14MSQ2 marksselect all that apply
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  1. M is an invertible matrix.
  2. M is a singular matrix.
  3. The determinant of M is 4.
  4. M is diagonalizable.
Q15MCQ2 marks
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  1. A is positive definite.
  2. A is positive semi-definite.
  3. A is negative definite.
  4. A is negative semi-definite.

Answer key

  1. Q1 (MSQ, 3 marks): B, C
  2. Q2 (MSQ, 3 marks): A, B, C
  3. Q3 (MCQ, 3 marks): B
  4. Q4 (MCQ, 3 marks): A
  5. Q5 (MCQ, 3 marks): A
  6. Q6 (MCQ, 3 marks): B
  7. Q7 (MCQ, 3 marks): B
  8. Q8 (MCQ, 2 marks): B
  9. Q9 (MCQ, 2 marks): D
  10. Q10 (MCQ, 2 marks): A
  11. Q11 (MCQ, 3 marks): A
  12. Q12 (MCQ, 3 marks): D
  13. Q13 (MCQ, 3 marks): A
  14. Q14 (MSQ, 2 marks): B, D
  15. Q15 (MCQ, 2 marks): B

Concepts this paper tests

Auto-generated summary from the source site. Handy as a checklist; the lessons above explain each idea from scratch.

Summary of Core Topics, Concepts, Principles, and Equations

1. Matrix Properties and Operations

2. Quadratic Forms and Covariance Matrices

3. Principal Component Analysis (PCA)

4. Gradient Descent Algorithm

5. Linear Algebra Concepts

Equations

Matrix Operations

  1. Conjugate Transpose:
BH=B‾TB^H = \overline{B}^T
  1. Eigenvalue Equation:
Av=αvA \mathbf{v} = \alpha \mathbf{v}
  1. Unitary Matrix Property:
A∗A=AA∗=IA^* A = A A^* = I
  1. Diagonalization:
A=QΛQTA = Q \Lambda Q^T
  1. Singular Value Decomposition (SVD):
A=Q1ΣQ2TA = Q_1 \Sigma Q_2^T
  1. Determinant of a 2x2 Matrix:
det(A)=ad−bc\text{det}(A) = ad - bc

Quadratic Forms

  1. Quadratic Form:
Q(x,y,z)=ax2+dy2+fz2+2bxy+2cxz+2eyzQ(x, y, z) = ax^2 + dy^2 + fz^2 + 2bxy + 2cxz + 2eyz
  1. Covariance Matrix:
C=1n∑i=1n(xi−xˉ)(xi−xˉ)TC = \frac{1}{n} \sum_{i=1}^{n} (x_i - \bar{x})(x_i - \bar{x})^T

Gradient Descent

  1. Gradient Descent Update:
(x,y)=(x,y)−η∇f(x,y)(x, y) = (x, y) - \eta \nabla f(x, y)

PCA

  1. Projection onto Principal Components:
x~i=QTxi\tilde{x}_i = Q^T x_i

Graph 1: Matrix Properties and Operations

Graph 2: Quadratic Forms and Covariance Matrices

Graph 3: Principal Component Analysis (PCA)

Graph 4: Gradient Descent Algorithm

Graph 5: Linear Algebra Concepts

These graphs and summaries should help you understand the core topics and their relationships for the exam.