## 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.

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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

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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.

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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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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

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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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