Introduction to Machine Learning – IITKGP Week 1 NPTEL Assignment Answers 2025
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✅ Subject: Introduction to Machine Learning – IITKGP (nptel ml Answers)
📅 Week: 1
🎯 Session: NPTEL 2025 July-October
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NPTEL Introduction to Machine Learning – IITKGP Week 1 Assignment Answers 2025
1. 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
2. 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
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3. 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 : For Answers Click Here
4. 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 :
5. 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
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6. 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 :
7.
Answer :
8. 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 :
9. 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 :
10. Identify whether the following statement is true or false?
“Occam’s Razor is an example of Inductive Bias”
A. True
B. False
Answer : For Answers Click Here
NPTEL Introduction to Machine Learning – IITKGP Week 1 Assignment Answers 2024
1. Which of the following is a classification task?
A. Detect pneumonia from chest X-ray image
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 amount of rainfall
Answer: A
Explanation: Classification involves predicting categories or labels. Detecting pneumonia is a binary classification: pneumonia or not.
2. Which of the following is not a type of supervised learning?
A. Classification
B. Regression
C. Clustering
D. None of the above
Answer: C
Explanation: Clustering is an unsupervised learning technique. Classification and regression are supervised learning methods.
3. 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
Explanation: Finding the shortest path is solved using deterministic algorithms (like Dijkstra’s), not ML. Others involve prediction, suitable for ML.
4. Suppose I have 10,000 emails in my mailbox out of which 300 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 = 33.33%, Recall = 25%
B. Precision = 25%, Recall = 33.33%
C. Precision = 33.33%, Recall = 16.66%
D. Precision = 75%, Recall = 33.33%
Answer: C
Explanation:
- Precision = TP / (TP + FP) = 50 / 150 = 33.33%
- Recall = TP / (TP + FN) = 50 / 300 = 16.66%
5. Which of the following is/are supervised learning problems?
A. Predicting disease from blood samples.
B. Grouping students in the same class based on similar features.
C. Face recognition to unlock your phone.
Answer: A, C
Explanation: Supervised learning requires labeled data. (A) and (C) have defined labels (disease/no disease, person identity), while (B) is clustering.
6. Aliens challenge you to a complex game… Which machine learning paradigm should you choose for this?
A. Supervised learning
B. Unsupervised learning
C. Reinforcement learning
D. Use a random number generator and hope for the best
Answer: C
Explanation: Reinforcement learning is ideal for decision-making tasks where an agent learns via interaction and reward feedback — like playing a new game.
7. How many Boolean functions are possible with N features?
A. (2<sup>2<sup>N</sup></sup>)
B. (2<sup>N</sup>)
C. (N<sup>2</sup>)
D. (4N)
Answer: A
Explanation: A Boolean function maps every possible input combination to True/False. There are 2<sup>N</sup> input combinations, and each can be mapped in 2 ways → 2<sup>2<sup>N</sup></sup>.
8. 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
Explanation: The validation set is used for hyperparameter tuning and to prevent overfitting during training.
9. Regarding bias and variance, which of the following statements are true?
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, D
Explanation:
- Overfitting → low bias, high variance
- Underfitting → high bias, low variance
10. Which of the following is a categorical feature?
A. Height of a person
B. Price of petroleum
C. Mother tongue of a person
D. Amount of rainfall in a day
Answer: C
Explanation: Categorical features represent discrete groups. “Mother tongue” is qualitative, while the others are numerical.
