NPTEL Introduction To Machine Learning IITKGP ASSIGNMENT 1 Answers:– Hello students in this article we are going to share NPTEL Introduction To Machine Learning – IITKGP assignment week 1 answers. All the Answers provided below to help the students as a reference, You must submit your assignment at your own knowledge.
About Introduction To Machine Learning IITKGP Course:-
This course provides a concise introduction to the fundamental concepts in machine learning and popular machine learning algorithms. We will cover the standard and most popular supervised learning algorithms including linear regression, logistic regression, decision trees, k-nearest neighbour, an introduction to Bayesian learning and the naïve Bayes algorithm, support vector machines and kernels and neural networks with an introduction to Deep Learning. We will also cover the basic clustering algorithms. Feature reduction methods will also be discussed. We will introduce the basics of computational learning theory.
Criteria to get Certificate:-
Average assignment score = 25% of average of best 6 assignments out of the total 8 assignments given in the course.
Exam score = 75% of the proctored certification exam score out of 100
Final score = Average assignment score + Exam score
YOU WILL BE ELIGIBLE FOR A CERTIFICATE ONLY IF AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75. If one of the 2 criteria is not met, you will not get the certificate even if the Final score >= 40/100.
Certificate will have your name, photograph and the score in the final exam with the breakup.It will have the logos of NPTEL and IIT Kharagpur.It will be e-verifiable at nptel.ac.in/noc.
Only the e-certificate will be made available. Hard copies will not be dispatched.
Once again, thanks for your interest in our online courses and certification. Happy learning.
Below you can find NPTEL INTRODUCTION TO MACHINE LEARNING IIT KGP Assignment 1 Answers
| Assignment No. | Answers |
|---|---|
| Introduction To Machine Learning – IITKGP Assignment 1 | Click Here |
| Introduction To Machine Learning – IITKGP Assignment 2 | Click Here |
| Introduction To Machine Learning – IITKGP Assignment 3 | Click Here |
| Introduction To Machine Learning – IITKGP Assignment 4 | Click Here |
| Introduction To Machine Learning – IITKGP Assignment 5 | Click Here |
| Introduction To Machine Learning – IITKGP Assignment 6 | Click Here |
| Introduction To Machine Learning – IITKGP Assignment 7 | Click Here |
| Introduction To Machine Learning – IITKGP Assignment 8 | Click Here |
NPTEL Introduction To Machine Learning IITKGP ASSIGNMENT 1 Answers 2022 :-
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
Answer:-b
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
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:-b
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
Answer:-b
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
Next Week Assignment Answers
Answer:-d
7. How many Boolean functions are possible with n features?
A. (22)
B. (2)
C. (N²)
D. (4)
Answer:-a
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
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:-b,c
10.Identify whether the following statement is true or false? “Occam’s Razor is an example of
Inductive Bias”
A. True
B. False
Answer:-a
For Internship:- Click Here
Disclaimer: We do not claim 100% surety of answers, these answers are based on our sole knowledge, and by posting these answers we are just trying to help students, so we urge do your assignment on your own.
if you have any suggestions then comment below or contact us at [email protected]
If you found this article Interesting and helpful, don’t forget to share it with your friends to get this information.
