# NPTEL Deep Learning – IIT Ropar Week 2 Assignment Answers 2024

## NPTEL Deep Learning – IIT Ropar Week 2 Assignment Answers 2024

1. Which of the following statements about the sigmoid function is NOT true?

• The derivative of the sigmoid function can be negative.
• The sigmoid function is continuous and differentiable.
• The sigmoid function maps any input value to a value between 0 and 1.
• The sigmoid function can be used as an activation function in neural networks.
`Answer :- For Answer Click Here`

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

• 65,536
• 8
• 256
• 64
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3. How many neurons do you need in the hidden layer of a perceptron to learn any boolean function with 4 inputs? (Only one hidden layer is allowed)

• 16
• 64
• 56
• 32
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4. 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 :- `

5. 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 :- `

6. 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.
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`Answer :- `

8. Suppose we have a function f(x1,x2)=x21+3×2+25 which we want to minimize the given function using the gradient descent algorithm. We initialize (x1,x2)=(0,0). What will bethe value of x1 after ten updates in the gradient descent process?(Let η be 1)

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

10. What is the purpose of the gradient descent algorithm in machine learning?

• To minimize the loss function
• To maximize the loss function
• To minimize the output function
• To maximize the output function
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