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NPTEL INTRODUCTION TO MACHINE LEARNING ASSIGNMENT 2 Answers 2022

• by QuizXp Team
• July 30, 2022 July 30, 2022

NPTEL INTRODUCTION TO MACHINE LEARNING ASSIGNMENT 2 Answers :- Hello students in this article we are going to share NPTEL INTRODUCTION TO MACHINE LEARNING assignment week 2 answers. All the Answers provided below to help the students as a reference, You must submit your assignment at your own knowledge.

Below you can find NPTEL INTRODUCTION TO MACHINE LEARNING Assignment 2 Answers

NPTEL INTRODUCTION TO MACHINE LEARNING Assignment 2 Answers 2022:-

1. The parameters obtained in linear regression a. can take any value in the real space b. are strictly integers c. always lie in the range [0,1] d. can take only non-zero values

2. Suppose that we have N independent variables ( X 1, X 2,… Xn ) and the dependent variable is Y . Now imagine that you are applying linear regression by fitting the best fit line using the least square error on this data. You found that the correlation coefficient for one of its variables (Say X 1) with Y is -0.005. a. Regressing Y on X 1 mostly does not explain away Y . b. Regressing Y on X 1 explains away Y . c. The given data is insufficient to determine if regressing Y on X 1 explains away Y or not.

3. Consider the following five training examples

We want to learn a function f ( x ) of the form f ( x )= ax + b which is parameterised by ( a , b ).Using mean squared error as the loss function, which of the following parameters would you use to model this function to get a solution with the minimum loss? a. (4, 3) b. (1, 4) c. (4, 1) d. (3, 4)

4. The relation between studying time (in hours) and grade on the final examination (0-100) in a random sample of students in the Introduction to Machine Learning Class was found to be: Grade = 30.5 + 15.2 (h)

How will a student’s grade be affected if she studies for four hours?

a. It will go down by 30.4 points. b. It will go down by 30.4 points. c. It will go up by 60.8 points. d. The grade will remain unchanged.

e.It cannot be determined from the information given

5. Which of the statements is/are True?

a. Ridge has sparsity constraint, and it will drive coefficients with low values to 0. b. Lasso has a closed form solution for the optimization problem, but this is not the case for Ridge. c. Ridge regression does not reduce the number of variables since it never leads a coefficient to zero but only minimizes it. d. If there are two or more highly collinear variables, Lasso will select one of them randomly.

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6. Consider the following statements:

Assertion(A): Orthogonalization is applied to the dimensions in linear regression. Reason(R): Orthogonalization makes univariate regression possible in each orthogonal dimension separately to produce the coefficients.

a. Both A and R are true, and R is the correct explanation of A. b. Both A and R are true, but R is not the correct explanation of A. c. A is true, but R is false. d. A is false, but R is true

e.Both A and R are false.

7. Consider the following statements:

Statement A: In Forward stepwise selection, in each step, that variable is chosen which has the maximum correlation with the residual, then the residual is regressed on that variable, and it is added to the predictor.

Statement B: In Forward stagewise selection, the variables are added one by one to the previously selected variables to produce the best fit till then

a. Both the statements are True. b. Statement A is True, and Statement B is False c. Statement A if False and Statement B is True d. Both the statements are False.

8. The linear regression model y = a 0+ a 1 x 1+ a 2 x 2+…+ apxp is to be fitted to a set of N training data points having p attributes each. Let X be N ×( p +1) vectors of input values (augmented by 1‘s), Y be N ×1 vector of target values, and θ be ( p +1)×1 vector of parameter values ( a 0, a 1, a 2,…, ap ). If the sum squared error is minimized for obtaining the optimal regression model, which of the following equation holds?

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Nptel introduction to machine learning assignment answers week 8 2022 iitkgp.

Dear students, are you looking for help in Machine Learning NPTEL week 8 assignment answers? So, here in this article, we have provided Machine Learning week 8 assignment answer’s hint.

NPTEL Introduction to Machine Learning Assignment Answers Week 8

Q1. For two runs of K-Mean clustering is it expected to get same clustering results?

a. Yes b. No

Answer: b. No

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Q2. Which of the following can act as possible termination conditions in K-Means?

I.For a fixed number of iterations.

II. Assignment of observations to clusters does not change between iterations. Except for cases with a bad local minimum.

III. Centroids do not change between successive iterations.

IV. Terminate when RSS falls below a threshold

A. I, III and IV

B. I, II and III

C. I, II and IV

D. All of the above

Answer : D. All of the above

Q3. After performing K-Means Clustering analysis on a dataset, you observed the following dendrogram. Which of the following conclusion can be drawn from the dendrogram?

a.There were 28 data points in clustering analysis.

b. The best no. of clusters for the analysed data points is 4.

c. The proximity function used is Average-link clustering.

d. The above dendrogram interpretation is not possible for K-Means clustering analysis.

Answer : d. The above dendrogram interpretation is not possible for K-Means clustering analysis.

Q4. What should be the best choice of no. of clusters based on the following results:

Answer: c. 3

Q5. Given, six points with the following attributes:

Which of the following clustering representations and dendrogram depicts the use of MIN or Single link proximity function in hierarchical clustering:

Answer: Option A

Q6. Is it possible that assignment of observations to clusters does not change between successiveiterations of K-means?

c. Can’t say

d. None of these

Answer: a. Yes

Q7. What is the possible reason(s) for producing two different dendograms using agglomerative clustering for the same data set?

a. Proximity function

b. No. of data points

c. Variables used

d. All of these

Answer: d. All of these

Q8. Which of the following algorithms suffer from the problem of convergence at local optima?

I. K-means clustering

II. Agglomerative clustering

III. Expectation-minimization clustering

IV. Divisive clustering

a. I and II

b. II and III

c. III and IV

d. I and III

Answer: d. I and III

Q9. Which of the following is/are valid iterative strategy before performing clustering analysis for treating missing values?

a. Imputation with mean

b. Nearest neighbour assignment

c. Imputation with expectation-maximization algorithm

Answer : c. Imputation with expectation-maximization algorithm

Q10. If two variables V1 and V2 are used for clustering, which of the following is/are true with K means clustering algorithm for K=3?

I. If V1 and V2 have a correlation of 1, cluster centroid will be in a straight line.

II. If V1 and V2 have a correlation of 0, cluster centroid will be in a straight line.

c. I and II

Answer: a. I only

Disclaimer: These answers are provided only for the purpose to help students to take references. This website does not claim any surety of 100% correct answers. So, this website urges you to complete your assignment yourself.

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NPTEL Introduction to Machine Learning Assignment Answers Week 7

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NPTEL Introduction to Machine Learning Assignment 6 Answers 2022

NPTEL Introduction to Machine Learning Assignment 6 Answers 2022:-  In This article, we have provided the answers of Introduction to Machine Learning Assignment 5 You must submit your assignment to your own knowledge.

About Introduction To Machine Learning

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. CRITERIA TO GET A CERTIFICATE Average assignment score = 25% of the average of best 8 assignments out of the total 12 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 THE 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.

NPTEL Introduction to Machine Learning Assignment 6 Answers 2022 {July – Dec}

1. Which of the following properties are characteristic of decision trees? a. Low bias b. High variance c. Lack of smoothness of prediction surfaces d. Unbounded parameter set

2. Consider the following dataset : What is the initial entropy of Malignant? a. 0.543 b. 0.9798 c. 0.8732 d. 1

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3. For the same dataset, what is the info gain of Vaccination? a. 0.4763 b. 0.2102 c. 0.1134 d. 0.9355

4. Consider the following statements: Statement 1: Decision Trees are linear non-parametric models. Statement 2: A decision tree may be used to explain the complex function learned by a neural network. a. Both the statements are True. b. Statement 1 is True, but Statement 2 is False. c. Statement 1 is False, but Statement 2 is True. d. Both the statements are False.

5. Which of the following machine learning models can solve the XOR problem without any transformations on the input space? a. Linear Perceptron b. Neural Networks b. Decision Trees d. Logistic Regression

6. Which of the following is/are major advantages of decision trees over other supervised learning techniques (Note that more than one choices may be correct) a. Theoretical guarantees of performance b. Higher performance c. Interpretability of classifier d. More powerful in its ability to represent complex functions

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7. Consider a dataset with only one attribute(categorical). Suppose there are q unordered values in this attribute. How many possible combinations are needed to find the best split-point for building the decision tree classifier? a. q b. q 2 c. 2 q-1 d. 2 q-1 – 1

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NPTEL Introduction to Machine Learning Assignment 6 Answers 2022:-

Q1.  Which of the following is very interpretable?

Answer:-   b

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Q2.  Which of these models are non-parametric?

Answer:- b, c

Q3.  Entropy for a 50-50 split between two classes is:

Q4.  Statement: Decision Tree is an unsupervised learning algorithm. Reason: The splitting criterion use only the features of the data to calculate their respective measures

Q5.  Having built a decision tree, we are using reduced error pruning to reduce the size of the tree. We select a node to collapse. For this particular node, on the left branch, there are three training data points with the following outputs: 5, 7, 9.6, and for the right branch, there are four training data points with the following outputs: 8.7, 9.8, 10.5, 11.

The maximum value of the outputs of data points denotes the response of a branch. The original responses for data points along the two branches (left & right respectively) were  response _ left  and,  response _ right  and the new response after collapsing the node is  response _ new . What are the values for response left,  response _ right  and  response _ new  (numbers in the option are given in the same order)?

Q6.  Which among the following split-points for the  feature 1 would give the best split according to the information gain measure?

Q7.  For the same dataset, which among the following split-points for  feature 2 would give the best split according to the gini index measure?

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Q8.  Consider a dataset with only one attribute(categorical). Suppose, there are 10 unordered values in this attribute, how many possible combinations are needed to find the best split-point for building the decision tree classifier?

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Disclaimer :- We do not claim 100% surety of solutions, these solutions are based on our sole expertise, and by using posting these answers we are simply looking to help students as a reference, so we urge do your assignment on your own.

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NPTEL Introduction to Machine Learning Assignment 6 Answers 2022:-  In This article, we have provided the answers of Introduction to Machine Learning Assignment 5

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Introduction to Machine Learning : Week 12 Feedback Form

Introduction to machine learning : week 12 is live now.

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Introduction to Machine Learning : Week 11 Feedback Form

Introduction to machine learning : week 11 is live now.

Dear students The lecture videos for Week-11 have been uploaded for the course  Introduction to Machine Learning . The lectures can be accessed using the following link: https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=117&lesson=118 Practice Assignment for Week-11 is also uploaded and can be accessed from the following link:  https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=117&assessment=144   Assignment for Week-11 is also uploaded and can be accessed from the following link:  https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=117&assessment=167 The assignment has to be submitted on or before Wednesday, [07-04-2021, 23:59 IST].   As we have done so far, please use the discussion forums if you have any questions on this module. Note: Please check the due date of the assignments in the announcement and assignment page if you see any mismatch write to us immediately. -NPTEL Team

Introduction to Machine Learning : Assignment 9 Re-evaluation !!

Dear Learners, Re-evaluation has been done by making the weightage as 0 for Question 6 in Assignment 9. Students are requested to find their revised scores of Assignment 9 on the Progress page. Thanks & Regards, NPTEL Team

Introduction to Machine Learning : Week 10 Feedback Form

Introduction to machine learning : assignment 9 reevaluation.

Dear Learner, Assignment 9 submission of all students have been reevaluated by changing the answer for question number 6. Students are requested to find their revised scores of Assignment 9 in the Progress page. Thanks & Regards, -NPTEL Team.

Introduction to Machine Learning : Week 10 is live now!!

Dear students The lecture videos for Week-10 have been uploaded for the course  Introduction to Machine Learning . The lectures can be accessed using the following link: https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=110&lesson=111 Practice Assignment for Week-10 is also uploaded and can be accessed from the following link:  https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=110&assessment=142   Assignment for Week-10 is also uploaded and can be accessed from the following link:  https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=110&assessment=165 The assignment has to be submitted on or before Wednesday, [31-03-2021, 23:59 IST].   As we have done so far, please use the discussion forums if you have any questions on this module. Note: Please check the due date of the assignments in the announcement and assignment page if you see any mismatch write to us immediately. -NPTEL Team

Introduction to Machine Learning : Week 9 Feedback Form

Introduction to machine learning : assignment 7 reevaluation.

Dear Learner Assignment 7 submission of all students has been reevaluated after the ignoring question number 2. Students are requested to find their revised scores of Assignment 7 in the Progress page. Thanks & Regards, - NPTEL Team.

Introduction to Machine Learning : Week 9 is live now!!

Dear students The lecture videos for Week-9 have been uploaded for the course  Introduction to Machine Learning . The lectures can be accessed using the following link: https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=103&lesson=104 Practice Assignment for Week-9 is also uploaded and can be accessed from the following link:  https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=103&assessment=141   Assignment for Week-9 is also uploaded and can be accessed from the following link:  https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=103&assessment=163 The assignment has to be submitted on or before Wednesday, [24-03-2021, 23:59 IST].   As we have done so far, please use the discussion forums if you have any questions on this module. Note: Please check the due date of the assignments in the announcement and assignment page if you see any mismatch write to us immediately. -NPTEL Team

Dear Learner, Assignment 7 submission of all students has been reevaluated after the ignoring question number 4. Students are requested to find their revised scores of Assignment 7 in the Progress page. Thanks & Regards, -NPTEL Team.

Introduction to Machine Learning : Week 8 Feedback Form

Introduction to machine learning : week 8 is live now.

Dear students The lecture videos for Week-8 have been uploaded for the course  Introduction to Machine Learning . The lectures can be accessed using the following link: https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=96&lesson=97 Practice Assignment for Week-8 is also uploaded and can be accessed from the following link:  https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=96&assessment=140   Assignment for Week-8 is also uploaded and can be accessed from the following link:  https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=96&assessment=162 The assignment has to be submitted on or before Wednesday, [17-03-2021, 23:59 IST] .   As we have done so far, please use the discussion forums if you have any questions on this module. Note: Please check the due date of the assignments in the announcement and assignment page if you see any mismatch write to us immediately. -NPTEL Team

Introduction to Machine Learning : Week 7 Feedback Form

Introduction to machine learning : week 7 is live now.

Dear students The lecture videos for Week-7 have been uploaded for the course  Introduction to Machine Learning . The lectures can be accessed using the following link: https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=87&lesson=88 Practice Assignment for Week-7 is also uploaded and can be accessed from the following link:  https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=87&assessment=139   Assignment for Week-7 is also uploaded and can be accessed from the following link:  https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=87&assessment=159 The assignment has to be submitted on or before Wednesday, [10-03-2021, 23:59 IST].   As we have done so far, please use the discussion forums if you have any questions on this module. Note: Please check the due date of the assignments in the announcement and assignment page if you see any mismatch write to us immediately. -NPTEL Team

Introduction to Machine Learning : Week 6 Feedback Form

Introduction to machine learning : week 6 is live now.

Dear students The lecture videos for Week-6 have been uploaded for the course  Introduction to Machine Learning . The lectures can be accessed using the following link: https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=76&lesson=77 Practice Assignment for Week-6 is also uploaded and can be accessed from the following link:  https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=76&assessment=138   Assignment for Week-6 is also uploaded and can be accessed from the following link:  https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=76&assessment=156 The assignment has to be submitted on or before Wednesday, [03-03-2021, 23:59 IST].   As we have done so far, please use the discussion forums if you have any questions on this module. Note: Please check the due date of the assignments in the announcement and assignment page if you see any mismatch write to us immediately. -NPTEL Team

Introduction to Machine Learning : Week 5 Feedback Form

Introduction to machine learning : assignment 3 reevaluation.

Dear Learner, Assignment 3 submission of all students have been reevaluated by changing the answer for question number 8 . Students are requested to find their revised scores of Assignment 3 in the Progress page. Thanks & Regards, -NPTEL Team.

Introduction to Machine Learning : Week 5 is live now!!

Dear students The lecture videos for Week-5 have been uploaded for the course  Introduction to Machine Learning . The lectures can be accessed using the following link: https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=65&lesson=66 Practice Assignment for Week-5 is also uploaded and can be accessed from the following link:  https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=65&assessment=137   Assignment for Week-5 is also uploaded and can be accessed from the following link:  https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=65&assessment=154 The assignment has to be submitted on or before Wednesday, [24-02-2021, 23:59 IST] .   As we have done so far, please use the discussion forums if you have any questions on this module. Note: Please check the due date of the assignments in the announcement and assignment page if you see any mismatch write to us immediately. -NPTEL Team

Introduction to Machine Learning : Week 4 Feedback Form

Introduction to machine learning : assignment 1 reevaluation .

Dear Learner, Assignment 1 submission of all students have been reevaluated by adding the answer for question number 1 . Students are requested to find their revised scores of Assignment 1 in the Progress page. Thanks & Regards, -NPTEL Team.

Introduction to Machine Learning : Week 4 is live now!!

Dear students The lecture videos for Week-4 have been uploaded for the course  Introduction to Machine Learning . The lectures can be accessed using the following link: https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=55&lesson=56 Practice Assignment for Week-4 is also uploaded and can be accessed from the following link:  https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=55&assessment=136   Assignment for Week-4 is also uploaded and can be accessed from the following link:  https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=55&assessment=152 The assignment has to be submitted on or before Wednesday, [17-02-2021, 23:59 IST].   As we have done so far, please use the discussion forums if you have any questions on this module. Note: Please check the due date of the assignments in the announcement and assignment page if you see any mismatch write to us immediately. -NPTEL Team

Introduction to Machine Learning : Feedback on Text Transcripts (English) of NPTEL videos

Dear Learners, We have uploaded the English transcripts for this course already. We would like to hear from you, a quick feedback for the same. Please take a minute to fill out this form. Click here  to fill the form -NPTEL Team

Introduction to Machine Learning : Week 3 Feedback Form

Introduction to machine learning : week 3 is live now.

Dear students The lecture videos for Week-3 have been uploaded for the course  Introduction to Machine Learning . The lectures can be accessed using the following link: https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=45&lesson=46 Practice Assignment for Week-3 is also uploaded and can be accessed from the following link:  https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=45&assessment=135   Assignment for Week-3 is also uploaded and can be accessed from the following link:  https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=45&assessment=148 The assignment has to be submitted on or before Wednesday, [10-02-2021, 23:59 IST] .   As we have done so far, please use the discussion forums if you have any questions on this module. Note: Please check the due date of the assignments in the announcement and assignment page if you see any mismatch write to us immediately. -NPTEL Team

Introduction to Machine Learning : Assignment 2 due date has been extended!!

Dear Learners, Assignment 2  has been released already and the due date for the assignment has been extended Due date of assignment 2 is  Sunday, 07-02-2021, 23:59 IST Please note that there will not be any extension for the upcoming assignments. Note:  Please check the due date of the assignments in the announcement and assignment page if you see any mismatch write to us immediately.   Thanks & Regards, -NPTEL Team

Week 2 Feedback Form : Introduction to Machine Learning

Dear Learners, Thank you for continuing with the course and hope you are enjoying it. We would like to know if the expectations with which you joined this course are being met and hence please do take 2 minutes to fill out our weekly feedback form. It would help us tremendously in gauging the learner experience. Here is the link to the form:  https://docs.google.com/forms/d/1dnM4PbDMOxdQO7mUQSpKWNbFNn1OJ9ZLp-Szases-O8/viewform Thanks & Regards -NPTEL team

[NOC21-CS24] Clarification in Q8 of assignment 2

Dear Learner, In the 8th question of assignment-2, the representation vector for the word "Waffle" should be [6,4,0].  The given rules to find the feature vector are correct. In case of any doubt, feel free to ask on the forum. Regards, TAs

Introduction to Machine Learning : Week 2 is live now!!

Dear students The lecture videos for Week-2 have been uploaded for the course  Introduction to Machine Learning . The lectures can be accessed using the following link: https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=34&lesson=35 Practice Assignment for Week-2 is also uploaded and can be accessed from the following link:  https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=34&assessment=134   Assignment for Week-2 is also uploaded and can be accessed from the following link:  https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=34&assessment=147 The assignment has to be submitted on or before Wednesday, [03-02-2021, 23:59 IST].   As we have done so far, please use the discussion forums if you have any questions on this module. Note: Please check the due date of the assignments in the announcement and assignment page if you see any mismatch write to us immediately. -NPTEL Team

Week 1 Feedback Form : Introduction to Machine Learning

Introduction to machine learning : week 1 is live now.

Dear students The lecture videos for Week-1 have been uploaded for the course  Introduction to Machine Learning . The lectures can be accessed using the following link: https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=23&lesson=24 The other lectures in this week are accessible from the navigation bar to the left. Please remember to login into the website to view contents (if you aren't logged in already). Practice Assignment for Week-1 is also uploaded and can be accessed from the following link:  https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=23&assessment=133   Assignment for Week-1 is also uploaded and can be accessed from the following link:  https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=23&assessment=145 The assignment has to be submitted on or before Wednesday, [03-02-2021, 23:59 IST] .   As we have done so far, please use the discussion forums if you have any questions on this module. Note: Please check the due date of the assignments in the announcement and assignment page if you see any mismatch write to us immediately. -NPTEL Team

NPTEL: Exam Registration is open now for Jan 2021 courses!

Dear Learner,  Here is the much-awaited announcement on registering for the Jan 2021 NPTEL course certification exam.  1. The registration for the certification exam is open only to those learners who have enrolled in the course.  2. If you want to register for the exam for this course, login here using the same email id which you had used to enroll to the course in Swayam portal. Please note that Assignments submitted through the exam registered email id ALONE will be taken into consideration towards final consolidated score & certification.  3 .  Date of exam: April 25, 2021 Certification exam registration URL is:  https://examform.nptel.ac. in/   Choose from the Cities where exam will be conducted:  Exam Cities   4. Exam fees:  If you register for the exam and pay before  Mar 8, 2021, 10:00 AM,  Exam fees will be  Rs. 1000/- per exam .  If you register for exam before  Mar 8, 2021 , 10:00 AM  and have not paid or if you register between  Mar 8, 2021, 10:00 AM & Mar 12, 2021, 5:00 PM,  Exam fees will be  Rs. 1500/-  per exam  5. 50% fee waiver for the following categories:  Students belonging to the SC/ST category: please select Yes for the SC/ST option and upload the correct Community certificate. Students belonging to the PwD category with more than 40% disability: please select Yes for the option and upload the relevant Disability certificate.  6. Last date for exam registration: Mar 12, 2021 5:00 PM (Friday).  7. Mode of payment: Online payment - debit card/credit card/net banking.  8. HALL TICKET:  The hall ticket will be available for download tentatively by  2 weeks prior to the exam date .  We will confirm the same through an announcement once it is published.  9. FOR CANDIDATES WHO WOULD LIKE TO WRITE MORE THAN 1 COURSE EXAM:- you can add or delete courses and pay separately – till the date when the exam form closes. Same day of exam – you can write exams for 2 courses in the 2 sessions. Same exam center will be allocated for both the sessions.  10.  Data changes:  Last date for data changes: Mar 12, 2021, 5:00 PM:  All the fields in the Exam form except for the following ones can be changed until the form closes.  The following 6 fields can be changed ONLY when there are NO courses in the course cart. And you will be able to edit the following fields only if you: -  REMOVE unpaid courses from the cart And/or - CANCEL paid courses  1. Do you come under the SC/ST category? *  2. SC/ST Proof  3. Are you a person with disabilities? *  4. Are you a person with disabilities above 40%?  5. Disabilities Proof  6. What is your role ?  Note:  Once you remove or cancel a course, you will be able to edit these fields immediately.  But, for cancelled courses, refund of fees will be initiated only after 2 weeks.  11.  LAST DATE FOR CANCELLING EXAMS and getting a refund: Mar 12, 2021, 5:00 PM  12. Click here to view Timeline and Guideline :  Guideline    Thanks & Regards, NPTEL TEAM

Introduction to Machine Learning : Week 0 is live now!!

Dear Learners,  We welcome you all to this course Introduction to Machine Learning . The assignment 0 has been released.  This assignment is based on prerequisite of the course.  You can find the assignment in the link :  https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=16&assessment=132 Due date of assignment 0 is  25-01-2021, 23:59 IST. Please note that this assignment is for practice and it will not be graded . Thanks & Regards  -NPTEL Team

Introduction to Machine Learning : Week 1 videos are live now!!

Dear Learners, The lecture videos for Week-1 have been uploaded for the course Introduction to Machine Learning . The lectures can be accessed using the following link: https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=23&lesson=24 The other lectures in this week are accessible from the navigation bar to the left. Please remember to login into the website to view contents (if you aren't logged in already).   As we have done so far, please use the discussion forums if you have any questions on this module. - NPTEL Team

Welcome to NPTEL Online Course - Jan 2021!!

• Every week, about 2.5 to 4 hours of videos containing content by the Course instructor will be released along with an assignment based on this. Please watch the lectures, follow the course regularly and submit all assessments and assignments before the due date. Your regular participation is vital for learning and doing well in the course. This will be done week on week through the duration of the course.
• Please do the assignments yourself and even if you take help, kindly try to learn from it. These assignments will help you prepare for the final exams. Plagiarism and violating the Honor code will be taken very seriously if detected during the submission of assignments.
• The announcement group - will only have messages from course instructors and teaching assistants - regarding the lessons, assignments, exam registration, hall tickets etc.
• The discussion forum (Ask a question tab on the portal) - is for everyone to ask questions and interact.Anyone who knows the answers can reply to anyone's post and the course instructor/TA will also respond to your queries.
• Please make maximum use of this feature as this will help you learn much better.
• If you have any questions regarding the exam, registration, hall tickets, results, queries related to the technical content in the lectures, any doubts in the assignments, etc can be posted in the forum section
• The course is free to enroll and learn from. But if you want a certificate, you have to register and write the proctored exam conducted by us in person at any of the designated exam centres.
• The exam is optional for a fee of Rs 1000/- (Rupees one thousand only).
• Date and Time of Exams: April 25,2021 Morning session 9am to 12 noon; Afternoon Session 2pm to 5pm.
• Registration url: Announcements will be made when the registration form is open for registrations.
• The online registration form has to be filled and the certification exam fee needs to be paid. More details will be made available when the exam registration form is published. If there are any changes, it will be mentioned then.
• Please check the form for more details on the cities where the exams will be held, the conditions you agree to when you fill the form etc.
• Once again, thanks for your interest in our online courses and certification. Happy learning. 

NPTEL : Keep in touch with us via Social Media

Dear Learner You already must know NPTEL is providing course certificates to those who complete the course successfully, with the learning happening right at your home or where you are. But NPTEL also keeps bringing out new initiatives and courses - which we would like to keep you posted on. Click the below links to like and follow us on Social Media for instant Updates: Facebook: https://www.facebook.com/NPTELNoc Twitter: https://twitter.com/nptelindia Linkedin: https://www.linkedin.com/in/nptel-india-085866ba/ Instagram: https://www.instagram.com/swayam_nptel/  Like and Follow us on Social Media. Let's create a better future by learning and growing together.  -NPTEL Team.

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My Journey Through the NPTEL “Data Analytics with Python” Course

I recently completed the NPTEL course “Data Analytics with Python,” and I am thrilled to share my experience with you all. This 12-week journey was incredibly enlightening, and I am proud to say that I earned an Elite + Silver Certificate with an overall score of 85. The course was structured to provide a comprehensive understanding of Data analytics, and the hands-on experience with Python programming was invaluable.

Preparation Phase:

I enrolled in the course in the middle of January 2024, with classes beginning in January 2024. To get a head start, I previewed the course content available on YouTube, which included around 61 videos.

Starting in January 2024, NPTEL would unlock each week’s lectures gradually. I maintained a notebook from the start, diligently taking notes for future reference. Understanding the importance of the weekly assignments, I dedicated myself to completing them thoroughly, knowing that the top 8 would significantly impact my final score. Additionally, I used online resources like GeeksforGeeks to supplement my learning and clarify complex concepts. I attended the Online Live Doubt sessions from NPTEL every Saturday to get my doubts cleared.

Weekly Course Layout & Learning Journey:

The course was meticulously structured into weekly modules, each focusing on a different aspect of Data analytics and Python programming. Here’s a brief overview of what I learned each week:

Week 1: Introduction to data analytics and Python fundamentals

I started with the basics of Data analytics and Python programming. This week laid the groundwork, covering essential Python syntax and data structures. I practised by writing simple Python scripts and familiarizing myself with Python libraries like pandas and numpy.

Week 2: Introduction to Probability Two-way

In the second week, I delved into probability theory, a crucial component for understanding data distributions and statistical analysis. I used Python to solve various probability problems and visualize distributions.

Week 3: Sampling and sampling distributions

I explored sampling techniques and sampling distributions, which are fundamental for making inferences about larger populations from sample data. I applied these concepts by generating samples from datasets and analyzing their distributions.

Week 4: Hypothesis testing

This week focused on hypothesis testing, providing the tools to make decisions based on data analysis and statistical evidence. I conducted hypothesis tests using Python, enhancing my understanding of statistical significance.

Week 5: Two sample testing and introduction to ANOVA

I learned about two-sample tests and the basics of ANOVA (Analysis of Variance), which are essential for comparing means across different groups. I also implemented these tests on real-world datasets to compare group means. For various Datasets to practice on, you can explore Kaggle.

Week 6: Two-way ANOVA and linear regression

This week, I covered two-way ANOVA and was introduced to linear regression, a powerful technique for modelling relationships between variables. I practised by building linear regression models and interpreting their coefficients.

Week 7: Linear regression and multiple regression

Building on the previous week, I delved deeper into linear regression and multiple regression, enhancing my modelling skills. I used Python to perform multiple regression analyses, gaining insights into how multiple variables influence outcomes.

Week 8: Concepts of MLE and Logistic regression

I explored Maximum Likelihood Estimation (MLE) and logistic regression this week which is crucial for binary classification problems. I also applied logistic regression to classification problems, learning how to predict binary outcomes.

Week 9: ROC and Regression Analysis Model Building

In this week, I focused on ROC curves for evaluating classification models and regression analysis for building predictive models. I used ROC curves to assess the performance of my models, improving their accuracy.

Week 10: χ2 Test an introduction to cluster analysis

I learned about the chi-squared test for independence and an introduction to clustering techniques for unsupervised learning this week. I also performed chi-squared tests on categorical data and experimented with clustering algorithms like k-means.

Week 11: Clustering analysis

At the end of the course, I delved deeper into clustering analysis, covering various algorithms to group similar data points. I used clustering techniques to segment datasets into meaningful groups, discovering hidden patterns.

Week 12: Classification and Regression Trees (CART)

In the final week, I explored Classification and Regression Trees (CART), powerful tools for both classification and regression tasks. I built and evaluated decision trees, learning how to make predictive models more interpretable.

The Exam Day & Exam Experience:

27th April 2024, was the D-Day marked on my calendar with a mix of anticipation and anxiety. The admit card was in hand, and the examination venue was selected with care. The three-hour exam consisted of 50 questions, blending assignment-based problems and conceptual queries. Each Question carried 2 Marks. The strict invigilation at the centre ensured a fair testing environment. Despite facing some challenging questions, I approached each with determination, drawing on the solid foundation built through weekly assignments and intensive preparation. The best part was there was no Negative Marking, so you can guess some questions. Completing the exam was a moment of triumph, knowing that regardless of the results, I had gained invaluable knowledge and skills.

My 12 Week Course Experience:

For me, this course was easy and rewarding. Each week introduced new concepts that required dedication and persistence to master. The weekly assignments were crucial in reinforcing my understanding, and the final certification exam tested my comprehensive knowledge of the entire course.

One of the aspects I appreciated the most was the practical application of concepts through Python programming. Creating analytics models and solving real-world problems provided a hands-on experience that was immensely valuable for me. The course also included real-world examples of analytics in various industries, illustrating how these techniques can be applied in different contexts. It encouraged me to search & explore more such Techniques and examples.

I feel participating in the discussion forums was a highlight of my learning experience. Engaging with peers and instructors through NPTEL Live Doubt sessions helped clarify complex concepts and provided different perspectives on problem-solving. I highly recommend future aspirants to actively participate in these forums.

Criteria to get an NPTEL Course Completion Certificate:

Average assignment score = 25% of the average of the best 8 assignments out of the total 12 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 THE 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.

Conclusion:

Reflecting on my journey through the NPTEL “Data Analytics with Python” course, I am incredibly grateful for the experience. It has significantly deepened my knowledge of Data Analytics using Python and prepared me for future endeavours in this exciting field. The Elite + Silver Certificate I earned is a testament to the hard work and dedication I put into this course.

For anyone considering this course, I highly recommend it. The comprehensive curriculum and structured approach make it an invaluable learning experience. Enroll in this course if you can; I am sure you won’t regret it!

Happy Learning!

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