Neural Networks and Deep Learning

SNN MCQ in Python

⛪ Computer Science and Engineering > Neural Networks and Deep Learning

SNN MCQ in Python ➲ SNN MCQ in Python - Quiz

Q 1: In dot product the number of rows in first matrix must be equal to number of columns in second.

  • A False
  • B True

Q 2: What is the output of print(np.array([1,2,3]) +1)?

  • A [2 3 4]
  • B [11 21 31]
  • C [1 2 3 1]
  • D [1 1 2 3]

Q 3: In dot product between two matrix of shape (5,8) and (8,4) what would be the shape of resultant matrix?

  • A (8,8)
  • B (5,4)
  • C (8,5)
  • D (4,5)

Q 4: Which of the below formula is used to update weights while performing gradient descent?

  • A w - learning_rate*dw
  • B dw - learning_rate*w
  • C w /learning_rate*dw
  • D w +learning_rate*dw

Q 5: What is the output range of Sigmoid function?

  • A 0 to infinity
  • B -0.5 to 1
  • C -1 to + 1
  • D 0 to 1

Q 6: Broadcasting in Python throws error when you try to add two vectors of shape(1,5) and (1,6).

  • A False
  • B True

Q 7: A vector of size (n,1) is called a row vector.

  • A False
  • B True

Q 8: What is the output of print(np.dot([1,2,3],[[1],[2],[3]])?

  • A [[1 2 3] [2 4 6] [3 6 9]]
  • B throws error
  • C [[14]]
  • D [14]

Q 9: What is the output of print(np.array([1,2,3]) * np.array([1,2,3]) )?

  • A [14 14 14]
  • B [14]
  • C [1 4 9]
  • D [1 2 3 1 2 3]

Q 10: What does it mean if derivatives of parameter with respect to cost is zero?

  • A current parameter value must be increased
  • B current parameter value must be decreased
  • C cost function has reached its local minima
  • D None of the options

Q 11: For a single neuron network, if number of features is 5 then what would be the dimension of weight vector.

  • A (1,1)
  • B (1,5)
  • C (5,5)
  • D (5,1)