Deep Learning | Week 5

Course Name: Deep Learning

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These are NPTEL Deep Learning Week 5 Assignment 5 Answers


Q1. The activation function which is not analytically differentiable for all real values of the given input is
a. Sigmoid
b. Tanh
c. RelU
d. Both a&b

Answer: c. RelU


Q2. What is the main benefit of stacking multiple layers of neuron with non-linear activation functions over a single layer perceptron?
a. Reduces complexity of the network
b. Reduce inference time during testing
c. Allows to create non-linear decision boundaries
d. All of the above

Answer: c. Allows to create non-linear decision boundaries


These are NPTEL Deep Learning Week 5 Assignment 5 Answers


Q3. What will the output from node a3 in the following neural network setup when the inputs are (x1,x2) = (1,1).The activation function used in each of three nodes a,, a, and a; are zero- thresholdingi.e f(x) = 1if x > 0else 0?

image 57

a. -1
b. 0
c. 1
d. 0.5

Answer: c. 1


Q4. Suppose a neural network has 3 input 3 nodes, x, y, z. There are 2 neurons, Qand F. Q=4x +y and F = Q * z2. What is the gradient of F with respect to x, y and z? Assume, (x, y, z) = (-2, 5, -4).
a. (64,16, 24)
b. (-24,-4,16)
c. (4,4,-13)
d. (13,13,24)

Answer: a. (64,16, 24)


These are NPTEL Deep Learning Week 5 Assignment 5 Answers


Q5. Which of the following properties, if present in an activation function CANNOT be used in a neural network?
a. The function is periodic
b. The function is monotonic
c. The function is unbounded
d. Bothaandb

Answer: a. The function is periodic

See also  Deep Learning | Week 9

Q6. For a binary classification setting. what if the probability of belonging to class = +1 is 0.67 the probability of belonging to class= -1?
a. 0
b. 033
c. 0.67*0.33
d 1- (067 * 067)

Answer: b. 033


These are NPTEL Deep Learning Week 5 Assignment 5 Answers


Q7. Suppose a fully-connected neural network has a single hidden layer with 10 nodes. The input is represented by a 5D feature vector and the number of classes is 3. Calculate the number of 3 parameters of the network. Consider there are NO bias nodes in the network?
a. 80
b. 75
c. 78
d. 120

Answer: a. 80


These are NPTEL Deep Learning Week 5 Assignment 5 Answers


Q8. For a 2-class classification problem, what is the minimum number of nodes required for the output layer of a multi-layered neural network?
a. 2
b. 1
c. 3
d. None of the above

Answer: b. 1


These are NPTEL Deep Learning Week 5 Assignment 5 Answers


Q9. Suppose the input layer of a fully-connected neural network has 4 nodes. The value of a node in the first hidden layer before applying sigmoid nonlinearity is V. Now, each of the input layer’s nodes are called up by 8 times. What will be the value of that neuron with the updated input layer?
a. 8v
b. 4v
c. 32v
d. Remain same since scaling of input layers does not affect the hidden layers

Answer: a. 8v


These are NPTEL Deep Learning Week 5 Assignment 5 Answers


Q10. Which of the following are potential benefits of using ReLU activation over sigmoid activation?
a. Relu helps in creating dense (most of the neurons are active) representations
b. Relu helps in creating sparse (most of the neurons are non-active) representations
c. Relu helps in mitigating vanishing gradient effect
d. Both (b) and (c)

See also  Deep Learning | Week 6

Answer: d. Both (b) and (c)



These are NPTEL Deep Learning Week 5 Assignment 5 Answers

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These are NPTEL Deep Learning Week 5 Assignment 5 Answers