Hello learners In this article we are going to discuss NPTEL Deep Learning Assignment 1 Answers. All the Answers provided below to help the students as a reference, You must submit your assignment with your own knowledge and use this article as reference only.
About the course:-
Deep Learning has received a lot of attention over the past few years and has been employed successfully by companies like Google, Microsoft, IBM, Facebook, Twitter etc. to solve a wide range of problems in Computer Vision and Natural Language Processing. In this course we will learn about the building blocks used in these Deep Learning based solutions. Specifically, we will learn about feed forward neural networks, convolutional neural networks, recurrent neural networks and attention mechanisms.
| Assignment No. | Answers |
|---|---|
| Deep Learning IIT Ropar Assignment 1 | Click Here |
| Deep Learning IIT Ropar Assignment 2 | Click Here |
| Deep Learning IIT Ropar Assignment 3 | Click Here |
| Deep Learning IIT Ropar Assignment 4 | Click Here |
| Deep Learning IIT Ropar Assignment 5 | Click Here |
| Deep Learning IIT Ropar Assignment 6 | Click Here |
| Deep Learning IIT Ropar Assignment 7 | Click Here |
| Deep Learning IIT Ropar Assignment 8 | Click Here |
| Deep Learning IIT Ropar Assignment 9 | Click Here |
| Deep Learning IIT Ropar Assignment 10 | Click Here |
| Deep Learning IIT Ropar Assignment 11 | Click Here |
| Deep Learning IIT Ropar Assignment 12 | Click Here |
NPTEL Deep Learning Assignment 1 Answers 2023:
1. The table below shows the temperature and humidity data for two cities. Is the data linearly separable?
Yes
No
Cannot be determined from the given information
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2. What is the perceptron algorithm used for?
Clustering data points
Finding the shortest path in a graph
Classifying data
Solving optimization problems
Answer:-
3. What is the most common activation function used in perceptrons?
Sigmoid
ReLU
Tanh
Step
Answer:-
Next Week Answers: Assignment 02
4. Which of the following Boolean functions cannot be implemented by a perceptron?
AND
OR
XOR
NOT
Answer:_
5. We are given 4 points in R2 say, x1=(0,1),x2=(−1,−1),x3=(2,3),x4=(4,−5).Labels of x1,x2,x3,x4 are given to be −1,1,−1,1 We initiate the perceptron algorithm with an initial weight w0=(0,0) on this data. What will be the value of w0 after the algorithm converges? (Take points in sequential order from x1 to x)( update happens when the value of weight changes) (0,0)
(−2,−2)
(−2,−3)
(1,1)
Answer:_
6. We are given the following data:
Can you classify every label correctly by training a perceptron algorithm? (assume bias to be 0 while training)
Yes
No
Answer:_
7. Suppose we have a boolean function that takes 5 inputs x1,x2,x3,x4,x5? We have an MP neuron with parameter θ=1. For how many inputs will this MP neuron give output y=1
21
31
30
32
Answer:_
8. Which of the following best represents the meaning of term “Artificial Intelligence”?
The ability of a machine to perform tasks that normally require human intelligence
The ability of a machine to perform simple, repetitive tasks
The ability of a machine to follow a set of pre-defined rules
The ability of a machine to communicate with other machines
Answer:_
9. Which of the following statements is true about error surfaces in deep learning?
They are always convex functions.
They can have multiple local minima.
They are never continuous.
They are always linear functions.
Answer:_
10. What is the output of the following MP neuron for the AND Boolean function?
y={1,0,if x1+x2+x3≥1otherwisey=1 for (x1,x2,x3)=(0,1,1) y=0 for (x1,x2,x3)=(0,0,1) y=1 for (x1,x2,x3)=(1,1,1) y=0 for (x1,x2,x3)=(1,0,0)
Answer:_
