## NPTEL Deep Learning – IIT Ropar Week 2 Assignment Answer 2023

In this post, We have provided answers of NPTEL Deep Learning – IIT Ropar Assignment 1. We provided answers here only for reference. Plz, do your assignment at your own knowledge.

## NPTEL Deep Learning – IIT Ropar Week 2 Assignment Answer 2023

**1. What is the range of the sigmoid function σ(x)=1/1+e ^{−x}? **

- (−1,1)
- (0,1)
- −∞,∞)
- (0,∞)

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**2. What happens to the output of the sigmoid function as |x| very small?**

- The output approaches 0.5
- The output approaches 1.
- The output oscillates between 0 and 1.
- The output becomes undefined.

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**3. Which of the following theorem states that a neural network with a single hidden layer containing a finite number of neurons can approximate any continuous function?**

- Bayes’ theorem
- Central limit theorem
- Fourier’s theorem
- Universal approximation theorem

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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. A neural network has two hidden layers with 5 neurons in each layer, and an output layer with 3 neurons, and an input layer with 2 neurons. How many weights are there in total? (Dont assume any bias terms in the network)**

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**6. What is the derivative of the ReLU activation function with respect to its input at 0?**

- 0
- 1
- −1
- Not differentiable

Answer :-

**7. Consider a function f(x)=x ^{3}−3x^{2}+2. What is the updated value of xafter 3rd iteration of the gradient descent update, if the learning rate is 0.10.1 and the initial value of x is 4?**

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**8. Which of the following statements is true about the representation power of a multilayer network of sigmoid neurons?**

- A multilayer network of sigmoid neurons can represent any Boolean function.
- A multilayer network of sigmoid neurons can represent any continuous function.
- A multilayer network of sigmoid neurons can represent any function.
- A multilayer network of sigmoid neurons can represent any linear function.

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

- 65,536
- 82
- 56
- 64

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**10. How many neurons do you need in the hidden layer of a perceptron to learn any boolean function with 6 inputs? (Only one hidden layer is allowed)**

- 16
- 64
- 16
- 32

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Course Name | Deep Learning – IIT Ropar |

Category | NPTEL Assignment Answer |

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