NPTEL Introduction to Machine Learning Assignment 1 Answer 2023

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NPTEL Introduction to Machine Learning Assignment

ABOUT THE COURSE :
With the increased availability of data from varied sources there has been increasing attention paid to the various data driven disciplines such as analytics and machine learning. In this course we intend to introduce some of the basic concepts of machine learning from a mathematically well motivated perspective. We will cover the different learning paradigms and some of the more popular algorithms and architectures used in each of these paradigms.

INTENDED AUDIENCE : This is an elective course. Intended for senior UG/PG students. BE/ME/MS/PhD

PREREQUISITES : We will assume that the students know programming for some of the assignments.If the students have done introductory courses on probability theory and linear algebra it would be helpful. We will review some of the basic topics in the first two weeks as well.

INDUSTRY SUPPORT : Any company in the data analytics/data science/big data domain would value this course

Next Week Assignment Answers

This course can have Associate in Nursing unproctored programming communication conjointly excluding the Proctored communication, please check announcement section for date and time. The programming communication can have a weightage of twenty fifth towards the ultimate score.

Final score = Assignment score + Unproctored programming exam score + Proctored Exam score

Assignment score = 25% of average of best 8 assignments out of the total 12 assignments given in the course.
( All assignments in a particular week will be counted towards final scoring – quizzes and programming assignments).
Unproctored programming exam score = 25% of the average scores obtained as part of Unproctored programming exam – out of 100
Proctored Exam score =50% of the proctored certification exam score out of 100

YOU WILL BE ELIGIBLE FOR A CERTIFICATE ONLY IF ASSIGNMENT SCORE >=10/25 AND
UNPROCTORED PROGRAMMING EXAM SCORE >=10/25 AND PROCTORED EXAM SCORE >= 20/50.

If any one of the 3 criteria is not met, you will not be eligible for the certificate even if the Final score >= 40/100.

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1 point

Which of the following is a supervised learning problem?

Grouping related documents from an unannotated corpus.

Predicting credit approval based on historical data.

Predicting if a new image has cat or dog based on the historical data of other images of cats and dogs, where you are supplied the information about which image is cat or dog.

Fingerprint recognition of a particular person used in biometric attendance from the fingerprint data of various other people and that particular person.

Answer : B

1 point

Which of the following are classification problems?

Predict the runs a cricketer will score in a particular match.

Predict which team will win a tournament.

Predict whether it will rain today.

Predict your mood tomorrow.

Answer : ALL

1 point

Which of the following is a regression task?

Predicting the monthly sales of a cloth store in rupees.

Predicting if a user would like to listen to a newly released song or not based on historical data.

Predicting the confirmation probability (in fraction) of your train ticket whose current status is waiting list based on historical data.

Predicting if a patient has diabetes or not based on historical medical records.

Predicting if a customer is satisfied or unsatisfied from the product purchased from ecommerce website using the the reviews he/she wrote for the purchased product.

Answer :

1 point

Which of the following is an unsupervised learning task?

Group audio files based on language of the speakers.

Group applicants to a university based on their nationality.

Predict a student’s performance in the final exams.

Predict the trajectory of a meteorite.

Answer : A

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1 point

Which of the following is a categorical feature?

Number of rooms in a hostel.

Gender of a person

Your weekly expenditure in rupees.

Ethnicity of a person

Area (in sq. centimeter) of your laptop screen.

The color of the curtains in your room.

Number of legs an animal.

Minimum RAM requirement (in GB) of a system to play a game like FIFA, DOTA.

Answer : B,D,F,G,H

1 point

Which of the following is a reinforcement learning task?

Learning to drive a cycle

Learning to predict stock prices

Learning to play chess

Leaning to predict spam labels for e-mails

Answer : C

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1 point

Let $X$ and $Y$ be a uniformly distributed random variable over the interval $[0, 4]$ and $[0, 6]$ respectively. If $X$ and $Y$ are independent events, then compute the probability, $P (m a x (X, Y) > 3)$

Answer : 2/3

1 point

Find the mean of 0-1 loss for the given predictions:

$1$

$0$

$1.5$

$0.5$

Answer : 0.625

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1 point

Which of the following statements are true? Check all that apply.

A model with more parameters is more prone to overfitting and typically has higher variance.

If a learning algorithm is suffering from high bias, only adding more training examples may not improve the test error significantly.

When debugging learning algorithms, it is useful to plot a learning curve to understand if there is a high bias or high variance problem.

If a neural network has much lower training error than test error, then adding more layers will help bring the test error down because we can fit the test set better.

Answer : A.C

1 point

Bias and variance are given by:

$E [\hat{f} (x)] - f (x), E [(E [\hat{f} (x)] - \hat{f} (x))^{2}]$

$E [\hat{f} (x)] - f (x), E [(E [\hat{f} (x)] - \hat{f} (x))]^{2}$

$(E [\hat{f} (x)] - f (x)) 2, E [(E [\hat{f} (x)] - \hat{f} (x))^{2}]$

$(E [\hat{f} (x)] - f (x)) 2, E [(E [\hat{f} (x)] - \hat{f} (x))]^{2}$

Answer :  D
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NPTEL Introduction to Machine Learning Assignment

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