NPTEL Deep Learning – IIT Ropar Week 2 Assignment Answers 2024

NPTEL Deep Learning – IIT Ropar Week 2 Assignment Answers 2024

1. How many boolean functions can be designed for 3 inputs?

• 8
• 16
• 256
• 64
`Answer :- c`

2. How many weights does a neural network have if it consists of an input layer with 2 neurons, three hidden layers each with 4 neurons, and an output layer with 2 neurons? Assume there are no bias terms in the network.

`Answer :- Click Here`

3. A function f(x) is approximated using 250 tower functions. What is the minimum number of neurons required to construct the network that approximates the function?

• 250
• 249
• 251
• 500
• 750
• 501
`Answer :- Click Here`

4. Given the following input values to a sigmoid neuron: x1:0.72,x2:0.49,x3:0.08,x4:0.53,andx5:0.27
, what labels will the sigmoid neuron predict for these inputs? (Answer in sequence from x1
to x5).

• [0, 1, 1, 1, 1]
• [1, 0, 0, 1, 0]
• [0, 1, 0, 1, 0]
• [1, 1, 0, 1, 0]
`Answer :- `

5. How many boolean functions can be designed for 4 inputs?

• 65,536
• 8
• 256
• 64
`Answer :- `

6. We have a function that we want to approximate using 150 rectangles (towers). How many neurons are required to construct the required network?

• 301
• 451
• 150
• 500
`Answer :- `

7. What happens to the output of the sigmoid function as |x| becomes very large for input x?Select all relevant operations

• The output approaches 0.5
• The output approaches 1.
• The output oscillates between 0 and 1.
• The output approaches 0.
`Answer :- Click Here`

8. We have a classification problem with labels 0 and 1. We train a logistic model and find out that ω0
learned by our model is -17. We are to predict the label of a new test point x using this trained model. If ωTx=1, which of the following statements is True?

• We cannot make any prediction as the value of ωTx does not make sense
• The label of the test point is 0.
• The label of the test point is 1.
• We cannot make any prediction as we do not know the value of x
`Answer :- `
`Answer :- `

10. Suppose we have a function f(x1,x2)=x21+3x2+25 which we want to minimize the given function using the gradient descent algorithm. We initialize (x1,x2)=(0,0) . What will be the value of x1 after ten updates in the gradient descent process?(Let η be 1)

• 0
• -3
• −4.5
• −3
`Answer :- Click Here`