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Introduction to Machine Learning Assignment Answers Week 1 2022 IITKGP

Introduction to Machine Learning banner on which Assignment answer texted.

Hey Student, Do you want any hint in the assignment of NPTEL Introduction to Machine Learning Week 1? If yes, then your choice is absolutely correct. Here, in this article, you will get the answer’s hint of the Introduction to Machine Learning assignment.

NPTEL Introduction to Machine Learning Assignment Answers Week 1

Q1. Which of the following are classification tasks?

a. Find the gender of a person by analyzing his writing style
b. Predict the price of a house based on floor area, number of rooms etc.
c. Predict the temperature for the next day
d. Predict the number of copies of a book that will be sold this month

Answer: a. Find the gender of a person by analyzing his writing style

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Q2. Which of the following is a not categorical feature?

a. Gender of a person

b. Height of a person

c. Types of Mountains

d. Nationality of a person

Answer: b. Height of a person


Q3. Which of the following tasks is NOT a suitable machine learning task?

a. Finding the shortest path between a pair of nodes in a graph

b. Predicting if a stock price will rise or fall

c. Predicting the price of petroleum

d. Grouping mails as spams or non-spams

Answer: a. Finding the shortest path between a pair of nodes in a graph


Q4. Suppose I have 10,000 emails in my mailbox out of which 200 are spams. The spam detection system detects 150 mails as spams, out of which 50 are actually spams. What is the precision and recall of my spam detection system?

a. Precision = 33.333%, Recall = 25%

b. Precision 25%, Recall = 33.33%

c. Precision = 33.33%, Recall = 75%

d. Precision = 75%, Recall = 33.33%

Answer: b. Precision 25%, Recall = 33.33%


Q5. A feature F1 can take certain values: A, B, C, D, E, F and represents the grade of students from a college. Which of the following statements is true in the following case?

a. Feature F1 is an example of a nominal variable.

b. Feature F1 is an example of ordinal variables.

c. It doesn’t belong to any of the above categories.

d. Both of these

Answer: b. Feature F1 is an example of ordinal variables.


Q6. One of the most common uses of Machine Learning today is in the domain of Robotics. Robotic tasks include a multitude of ML methods tailored towards navigation, robotic control and a number of other tasks. Robotic control includes controlling the actuators available to the robotic system. An example of this is control of a painting arm in automotive industries.
The robotic arm must be able to paint every corner in the automotive parts while minimizing the quantity of paint wasted in the process. Which of the following learning paradigms would you select for training such a robotic arm?

a. Supervised learning

b. Unsupervised learning

c. Combination of supervised and unsupervised learning

d. Reinforcement learning

Answer: d. Reinforcement learning


Q7. How many Boolean functions are possible with n features?

a. (22^N)

b. (2N)

c. (N2)

d.  (4N)

Answer: a. (22^N)


Q8. What is the use of Validation dataset in Machine Learning?

a. To train the machine learning model.

b. To evaluate the performance of the machine learning model

c. To tune the hyperparameters of the machine learning model

d. None of the above

Answer: c. To tune the hyperparameters of the machine learning model


Q9. Regarding bias and variance, which of the following statements are true? (Here ‘high’ and ‘low’ are relative to the ideal model.)

a. Models which overfit have a high bias.

b. Models which overfit have a low bias.

c. Models which underfit have a high variance.

d. Models which underfit have a low variance.

Answer: b. Models which overfit have a low bias.
c. Models which underfit have a high variance.


Q10. Identify whether the following statement is true or false?

“Occam’s Razor is an example of Inductive Bias”

a. True

b. False

Answer: a. True


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NPTEL Introduction to Machine Learning Assignment Answers Week 2

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