nptel introduction to machine learning assignment answers 2022

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NPTEL: Exam Registration is open now for Jan 2022 courses!

Dear Candidate,

Here is a golden opportunity for those who had previously enrolled in this course during the Jan 2021 semester, but could not participate in the exams or were absent/did not pass the exam for this course. This course is being reoffered in Jan 2022 and we are giving you another chance to write the exam in April 2022 and obtain a certificate based on NPTEL norms. Do not let go of this unique opportunity to earn a certificate from the IITs/IISc.

IMPORTANT instructions for learners - Please read this carefully  

1. The exam date for this course: April 24, 2022

2. Certification exam registration URL is: CLICK HERE

Please fill the exam form using the same Enrolled email id & make fee payment via the form, as before.

3. Choose from the Cities where exam will be conducted: Exam Cities  

4. You DO NOT have to re-enroll in the courses. 

5. You DO NOT have to resubmit Assignments OR participate in the non-proctored 

programming exams.

6. If you do enroll to Jan 2022 course, we will take the best average assignment scores/non-proctored programming exam score across the two semesters

Our suggestion:

- Please check once if you have >= 40/100  in average assignment score and also participate in the non-proctored programming exams that will be conducted during this semester in the course to become eligible for the e-certificate, wherever applicable.

- If not, please submit Assignments again in the Jan 2022 course & and also participate in the non-proctored programming exams to become eligible for the e-certificate.

- You can also submit Assignments again and participate in the non-proctored programming exams if you want to better your previous scores.

RECOMMENDATION: Please enroll to the Jan 2022 course and brush up your lessons for the exam.

7. Exam fees: 

If you register for the exam and pay before March 14, 2022, 10:00 AM, Exam fees will be Rs. 1000/- per exam . 

If you register for exam before March 14, 2022, 10:00 AM and have not paid or if you register between March 14, 2022, 10:00 AM & March 18, 2022, 10:00 AM, Exam fees will be Rs. 1500/- per exam 

8. 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. 

9. Last date for exam registration: March 18, 2022 10:00 AM (Friday). 

10. Mode of payment: Online payment - debit card/credit card/net banking. 

11. 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. 

12. 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. 

13. Data changes: 

Last date for data changes: March 18, 2022 10:00 AM :  

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. 

14. LAST DATE FOR CANCELLING EXAMS and getting a refund: March 18, 2022 10:00 AM  

15. Click here to view Timeline and Guideline : Guideline  

Domain Certification

Domain Certification helps learners to gain expertise in a specific Area/Domain. This can be helpful for learners who wish to work in a particular area as part of their job or research or for those appearing for some competitive exam or becoming job ready or specialising in an area of study.  

Every domain will comprise Core courses and Elective courses. Once a learner completes the requisite courses per the mentioned criteria, you will receive a Domain Certificate showcasing your scores and the domain of expertise. Kindly refer to the following link for the list of courses available under each domain: https://nptel.ac.in/noc/Domain/discipline.html

Outside India Candidates

Candidates who are residing outside India may also fill the exam form and pay the fees. Mode of exam and other details will be communicated to you separately.

Thanks & Regards, 

Thank you for learning with NPTEL!!

Dear Learner, Thank you for taking the course with NPTEL!! Hope you enjoyed the journey with us. The results for this course have been published and we are closing this course now.  You will still have access to the contents and assignments of this course, if you click on the course name from the "Mycourses" tab on swayam.gov.in. The discussion forum is being closed though and you cannot ask questions here. For any further queries please write to [email protected] . - Team NPTEL

Introduction to Machine Learning: Result Published!

• Hard copies of certificates will not be dispatched.
• The duration shown in the certificate will be based on the timeline of offering of the course in 2021, irrespective of which Assignment score that will be considered.

Feedback for Introduction to Machine Learning

Dear student, We are glad that you have attended the NPTEL online certification course. We hope you found the NPTEL Online course useful and have started using NPTEL extensively. In this regard, we would like to have feedback from you regarding our course and whether there are any improvements, you would like to suggest.   We are enclosing an online feedback form and would request you to spare some of your valuable time to input your observations. Your esteemed input will help us in serving you better. The link to give your feedback is: https://docs.google.com/forms/d/1c0IyKJNdR4pyBPYF9Scj7som_yjqOhHcVQulMJb_SSQ/viewform We thank you for your valuable time and feedback. Thanks & Regards, -NPTEL Team

Introduction to Machine Learning: Open now for exam registration July 2021!!

Dear Candidate, Here is a golden opportunity for those who had previously enrolled in this course during the  Jan 2021  semester, but could not participate in the exams or were absent/did not pass the exam for this course. This course is being reoffered in July 2021 and we are giving you another chance to write the exam in Sep/Oct 2021 and obtain a certificate based on NPTEL norms. Do not let go of this unique opportunity to earn a certificate from the IITs/IISc. IMPORTANT instructions for learners - Please read this carefully 1. The exam date for this course:  October 24, 2021 2. Certification exam registration URL is:  https://examform.nptel.ac.in/     Please fill the exam form using the  same Enrolled email id  & make fee payment via the form, as before. 3. Choose from the Cities where exam will be conducted:   Exam Cities 4. You DO NOT have to re-enroll in the courses.  5. You DO NOT have to resubmit Assignments OR participate in the non-proctored  programming exams. 6. If you do enroll to July 2021 course, we will take the best average assignment scores/non-proctored programming exam score across the two semesters Our suggestion: - Please check once if you have >= 40/100  in average assignment score and also participate in the non-proctored programming exams that will be conducted during this semester in the course to become eligible for the e-certificate, wherever applicable. - If not, please submit Assignments again in the July 2021 course & and also participate in the non-proctored programming exams to become eligible for the e-certificate. - You can also submit Assignments again and participate in the non-proctored programming exams if you want to better your previous scores. RECOMMENDATION:  Please enroll to the July 2021 course and brush up your lessons for the exam. 7.  Exam fees:  If you register for the exam and pay before  Sep 13, 2021, 10:00 AM , Exam fees will be  Rs. 1000/- per exam .  If you register for exam before  Sep 13, 2021, 10:00 AM  and have not paid or if you register between  Sep 13, 2021, 10:00 AM & Sep 17, 2021, 5:00 PM , Exam fees will be  Rs. 1500/-  per exam  8. 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.  9. Last date for exam registration: Sep 17, 2021, 5:00 PM (Friday).   10. Mode of payment: Online payment - debit card/credit card/net banking.  11.  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.  12. 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.  13.  Data changes:   Last date for data changes: Sep 17, 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.  14.  LAST DATE FOR CANCELLING EXAMS and getting a refund: Sep 17, 2021, 5:00 PM   15. Click here to view Timeline and Guideline :  Guideline   Domain Certification Domain Certification helps learners to gain expertise in a specific Area/Domain. This can be helpful for learners who wish to work in a particular area as part of their job or research or for those appearing for some competitive exam or becoming job ready or specialising in an area of study.     Every domain will comprise Core courses and Elective courses. Once a learner completes the requisite courses per the mentioned criteria, you will receive a Domain Certificate showcasing your scores and the domain of expertise. Kindly refer to the following link for the list of courses available under each domain:  https://nptel.ac.in/noc/Domain/discipline.html Thanks & Regards,  NPTEL TEAM

April 2021 NPTEL Exams have been postponed!

Dear learner Taking the current covid situation into consideration, the NPTEL exams scheduled to be conducted on 24/25 April stand postponed until further notice. We will keep you informed of the potential dates for the exams as the situation improves and we finalize the same. Thanks and Regards, NPTEL TEAM.

Exam Format - April 25,2021

Dear Candidate, ****This is applicable only for the exam registered candidates**** Type of exam will be available in the list: Click Here You will have to appear at the allotted exam center and produce your Hall ticket and Government Photo Identification Card (Example: Driving License, Passport, PAN card, Voter ID, Aadhaar-ID with your Name, date of birth, photograph and signature) for verification and take the exam in person.  You can find the final allotted exam center details in the hall ticket. The hall ticket is yet to be released . We will notify the same through email and SMS. Type of exam: Computer based exam (Please check in the above list corresponding to your course name) The questions will be on the computer and the answers will have to be entered on the computer; type of questions may include multiple choice questions, fill in the blanks, essay-type answers, etc. Type of exam: Paper and pen Exam  (Please check in the above list corresponding to your course name) The questions will be on the computer. You will have to write your answers on sheets of paper and submit the answer sheets. Papers will be sent to the faculty for evaluation. On-Screen Calculator Demo Link: Kindly use the below link to get an idea of how the On-screen calculator will work during the exam. https://tcsion.com/ OnlineAssessment/ ScientificCalculator/ Calculator.html NOTE: Physical calculators are not allowed inside the exam hall. -NPTEL Team

Introduction to Machine Learning : Week 12 Feedback Form

Introduction to machine learning : week 12 is live now.

Dear students The lecture videos for Week-12 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=122&lesson=123 Practice Assignment for Week-12 is also uploaded and can be accessed from the following link:  https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=122&assessment=143   Assignment for Week-12 is also uploaded and can be accessed from the following link:  https://onlinecourses.nptel.ac.in/noc21_cs24/unit?unit=122&assessment=169 The assignment has to be submitted on or before Wednesday, [14-04-2021, 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 : 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.
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Course Name: Introduction to Machine Learning

• About Course
• Certificate Type
• Toppers list
• Registration

Course abstract

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.

Course Instructor

Prof. Balaraman Ravindran

Teaching assistant(s).

Deepak Maurya

 Course Duration : Jan-Apr 2020

  view course,  syllabus,  enrollment : 18-nov-2019 to 03-feb-2020,  exam registration : 16-dec-2019 to 20-mar-2020,  exam date : 26-apr-2020,   course statistics will be published shortly, certificate eligible, certified category count, successfully completed, participation.

Category : Successfully Completed

Category : Elite

Category : Silver

Category : Gold

Final score calculation logic.

• Assignment Score = Average of best 8 out of 12 assignments.
• Final Score(Score on Certificate)= 75% of Exam Score + 25% of Assignment Score Note: We have taken best assignment score from Both Jan and July course

PRASHANT BARTAKKE 96%

COLLEGE OF ENGINEERING PUNE

AKSHIV SINGHLA 91%

ANUJA SOMTHANKAR 90%

THAKUR COLLEGE OF ENGINEERING AND TECHNOLOGY

AMAN BAGRECHA 89%

R V COLLEGE OF ENGINEERING

MANYA SINGH 89%

Indian Institute of Technology,Roorkee

AMAN KUMAR 88%

PANDYA VEDANT MANOHAR 86%

NIKHIL KUMAR 85%

NATIONAL INSTITUTE OF TECHNOLOGY PATNA

AAYUSH TOMAR 84%

YARRAMSETTI PAVAN SAI KONDALA RAO 84%

RAJIV GANDHI UNIVERSITY OF KNOWLEDGE TECHNOLOGIES

ANURAG TIWARI 83%

ASHUTOSH PANDEY 83%

ASHISH RANJAN 83%

ARYAN SHARMA 83%

ARYA COLLEGE OF ENGINEERING & INFORMATION TECHNOLOGY

SHIVANSHU SURENDRA SHRIVASTAVA 83%

NAGA KALYAN REPALLE 82%

KAUSTUV DEB 82%

SUPREME KNOWLEDGE FOUNDATION GROUP OF INSTITUTIONS

DR.K.KUMAR 82%

GOVERNMENT COLLEGE OF TECHNOLOGY

SURENDRA GUPTA 82%

SHRI GOVINDRAM SEKSARIA INSTITUTE OF TECHNOLOGY AND SCIENCES

KARTIKA 82%

GURU NANAK DEV ENGINEERING COLLEGE

ANOOP A NAIR 82%

Indian Institute of Science Education and Research, Thiruvananthapuram (IISER-Tvm)

NEHA CHAUDHARY 82%

UTTARAKHAND TECHNICAL UNIVERSITY

RISHAV ADARSH 82%

APARAJITH RAGHUVIR 81%

INDIAN INSTITUTE OF INFORMATION TECHNOLOGY, DESIGN AND MANUFACTURING, KANCHEEPURAM

VISHNURAJ R 81%

Indian Institute of Technology Madras

AYUSH KUMAR 81%

ADITYA DUBEY 81%

BANARAS HINDU UNIVERSITY

SHILPA D GHODE 80%

KAVIKULGURU INSTITUTE OF TECHNOLOGY AND SCIENCE

ANIKET SUJAY 80%

A SAMUEL MOSES 80%

Indian Institute of Technology,Madras

SUDHEER POOJARY 80%

SHUBHAM KUMAR 80%

SILAR MOHAMMED TANWIR 80%

SANAT BHARGAVA 80%

DEEPAK PUTREVU 80%

Indian Space Research Organization

ROMA GOEL 79%

INDIAN INSTITUTE OF INFORMATION TECHNOLOGY, NAGPUR

KRISHNA KUMAR SUTAR 79%

AAKASH KHEPAR 79%

ISHITA JAIN 79%

PEC UNIVERSITY OF TECHNOLOGY

ISHWARI SINGH RAJPUT 79%

MRIDULA KUMARI 79%

FAYAZUR RAHAMAN MOHAMMAD 78%

MAHATMA GANDHI INSTITUTE OF TECHNOLOGY

K M BHARATHVAJ 78%

NITISHA PRADHAN 78%

ADITYA KUMAR SINGH 78%

SHUBHAM SANJAYKUMAR MANE 78%

PRAGYA AGARWAL 78%

Noida Institute of Engineering and Technology

RAJKUMAR LAKSHMANAMOORTHY 78%

NIRO PROJECTS

JAGANATHAN ANNAMALAI PARAMESHWARAN 78%

VIGNESH S 78%

PRADEEP REDDY GOGULAMUDI 78%

VIT-AP UNIVERSITY

SAROJ KUMAR PANDA 78%

ABEENA A 77%

Amrita vishwa Vidyapeetham

SAISH BALAJI DESAI 77%

SHUBHRANGSHU GHOSH 77%

Tata Consultancy Services Pvt. Ltd.

AAJAZ AHMAD PADDER 77%

ARUN A V 77%

GOVT. MODEL ENGINEERING COLLEGE

BACHU BALA RAJU 77%

KESHAV MEMORIAL INSTITUTE OF TECHNOLOGY (KMIT)

SIVA PRASATH K S K 77%

Extreme Networks

AMAN SINGH 77%

KAMALAKAR BAPANAPALLI 77%

Not Working

Enrollment Statistics

Total enrollment: 42058, registration statistics, total registration : 2254, assignment statistics, feedback videos.

Score Distribution Graph - Legend

Assignment score: distribution of average scores garnered by students per assignment., exam score : distribution of the final exam score of students., final score : distribution of the combined score of assignments and final exam, based on the score logic..

NPTEL Introduction to Machine Learning Assignment 1 Answers 2023

In this post, We have provided answers of NPTEL Introduction to Machine Learning Assignment 1. We provided answers here only for reference. Plz, do your assignment at your own knowledge.

NPTEL Introduction To Machine Learning Week 1 Assignment Answer 2023

1. 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.

2. 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.

3. 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.

4. 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.

5. 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 p e rson
• 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.

6. 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

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

• None of the above

9. 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.

10. Bias and variance are given by :

• E[f^(x)]−f(x),E[(E[f^(x)]−f^(x)) 2 ]
• E[f^(x)]−f(x),E[(E[f^(x)]−f^(x))] 2
• (E[f^(x)]−f(x))2,E[(E[f^(x)]−f^(x)) 2 ]
• (E[f^(x)]−f(x))2,E[(E[f^(x)]−f^(x))] 2

NPTEL Introduction to Machine Learning Assignment 1 Answers 2022 [July-Dec]

1. Which of the following are supervised learning problems? (multiple may be correct) a. Learning to drive using a reward signal. b. Predicting disease from blood sample. c. Grouping students in the same class based on similar features. d. Face recognition to unlock your phone.

2. Which of the following are classification problems? (multiple may be correct) a. Predict the runs a cricketer will score in a particular match. b. Predict which team will win a tournament. c. Predict whether it will rain today. d. Predict your mood tomorrow.

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3. Which of the following is a regression task? (multiple options may be correct) a. Predict the price of a house 10 years after it is constructed. b. Predict if a house will be standing 50 years after it is constructed. c. Predict the weight of food wasted in a restaurant during next month. d. Predict the sales of a new Apple product.

4. Which of the following is an unsupervised learning task? (multiple options may be correct) a. Group audio files based on language of the speakers. b. Group applicants to a university based on their nationality. c. Predict a student’s performance in the final exams. d. Predict the trajectory of a meteorite.

5. Given below is your dataset. You are using KNN regression with K=3. What is the prediction for a new input value (3, 2)?

6. Which of the following is a reinforcement learning task? (multiple options may be correct)

7. Find the mean of squared error for the given predictions:

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

👇 For Week 02 Assignment Answers 👇

9. Bias and variance are given by:

10. Which of the following are true about bias and variance? (multiple options may be correct)

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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. 

COURSE LAYOUT

• Week 0:  Probability Theory, Linear Algebra, Convex Optimization – (Recap)
• Week 1:  Introduction: Statistical Decision Theory – Regression, Classification, Bias Variance
• Week 2:  Linear Regression, Multivariate Regression, Subset Selection, Shrinkage Methods, Principal Component Regression, Partial Least squares
• Week 3:  Linear Classification, Logistic Regression, Linear Discriminant Analysis
• Week 4:  Perceptron, Support Vector Machines
• Week 5:  Neural Networks – Introduction, Early Models, Perceptron Learning, Backpropagation, Initialization, Training & Validation, Parameter Estimation – MLE, MAP, Bayesian Estimation
• Week 6:  Decision Trees, Regression Trees, Stopping Criterion & Pruning loss functions, Categorical Attributes, Multiway Splits, Missing Values, Decision Trees – Instability Evaluation Measures
• Week 7:  Bootstrapping & Cross Validation, Class Evaluation Measures, ROC curve, MDL, Ensemble Methods – Bagging, Committee Machines and Stacking, Boosting
• Week 8:  Gradient Boosting, Random Forests, Multi-class Classification, Naive Bayes, Bayesian Networks
• Week 9:  Undirected Graphical Models, HMM, Variable Elimination, Belief Propagation
• Week 10:  Partitional Clustering, Hierarchical Clustering, Birch Algorithm, CURE Algorithm, Density-based Clustering
• Week 11:  Gaussian Mixture Models, Expectation Maximization
• Week 12:  Learning Theory, Introduction to Reinforcement Learning, Optional videos (RL framework, TD learning, Solution Methods, Applications)

CRITERIA TO GET A CERTIFICATE

Average assignment score = 25% of 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 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 1 Answers [Jan – June 2022]

Q1. Which of the following is a supervised learning problem? 

a. Grouping related documents from an unannotated corpus.  b. Predicting credit approval based on historical data  c. Predicting rainfall based on historical data  d. Predicting if a customer is going to return or keep a particular product he/she purchased from e-commerce website based on the historical data about the customer purchases and the particular product.  e. Fingerprint recognition of a particular person used in biometric attendance from the fingerprint data of various other people and that particular person

Answer:- b, c, d , e

Q2. Which of the following is not a classification problem? 

a. Predicting the temperature (in Celsius) of a room from other environmental features (such as atmospheric pressure, humidity etc).  b.Predicting if a cricket player is a batsman or bowler given his playing records.  c. Predicting the price of house (in INR) based on the data consisting prices of other house (in INR) and its features such as area, number of rooms, location etc.  d. Filtering of spam messages  e. Predicting the weather for tomorrow as “hot”, “cold”, or “rainy” based on the historical data wind speed, humidity, temperature, and precipitation.

Answer:- a, c

Q3. Which of the following is a regression task? (multiple options may be correct) 

a. Predicting the monthly sales of a cloth store in rupees.  b. Predicting if a user would like to listen to a newly released song or not based on historical data.  c. Predicting the confirmation probability (in fraction) of your train ticket whose current status is waiting list based on historical data.  d. Predicting if a patient has diabetes or not based on historical medical records.  e. Predicting if a customer is satisfied or unsatisfied from the product purchased from e-commerce website using the the reviews he/she wrote for the purchased product.

Q4. Which of the following is an unsupervised task? 

a. Predicting if a new edible item is sweet or spicy based on the information of the ingredients, their quantities, and labels (sweet or spicy) for many other similar dishes.  b. Grouping related documents from an unannotated corpus.  c. Grouping of hand-written digits from their image.  d. Predicting the time (in days) a PhD student will take to complete his/her thesis to earn a degree based on the historical data such as qualifications, department, institute, research area, and time taken by other scholars to earn the degree.  e. all of the above

Answer:- c, d

Q5. Which of the following is a categorical feature? 

a. Number of rooms in a hostel.  b. Minimum RAM requirement (in GB) of a system to play a game like FIFA, DOTA.  c. Your weekly expenditure in rupees.  d. Ethnicity of a person  e. Area (in sq. centimeter) of your laptop screen.  f. The color of the curtains in your room.

Answer:- d, f

Q6. 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(max(X,Y)>3

a. 1/6 b. 5/6 c. 2/3 d. 1/2 e. 2/6 f. 5/8 g. None of the above

NOTE:- Answers of  Introduction to Machine Learning Assignment 1 will be uploaded shortly and it will be notified on Telegram, So  JOIN NOW

Q7. Let the trace and determinant of a matrix A[acbd] be 6 and 16 respectively. The eigenvalues of A are

Q8. What happens when your model complexity increases? (multiple options may be correct) 

a. Model Bias decreases  b. Model Bias increases  c. Variance of the model decreases  d. Variance of the model increases

Answer:- a, d

Q9. A new phone, E-Corp X1 has been announced and it is what you’ve been waiting for, all along. You decide to read the reviews before buying it. From past experiences, you’ve figured out that good reviews mean that the product is good 90% of the time and bad reviews mean that it is bad 70% of the time. Upon glancing through the reviews section, you find out that the X1 has been reviewed 1269 times and only 172 of them were bad reviews. What is the probability that, if you order the X1, it is a bad phone? 

a. 0.136  b. 0.160  c. 0.360  d. 0.840  e. 0.773  f. 0.573  g. 0.181

Q10. Which of the following are false about bias and variance of overfitted and underfitted models? (multiple options may be correct) 

a. Underfitted models have high bias.  b. Underfitted models have low bias.  c. Overfitted models have low variance.  d. Overfitted models have high variance.

NPTEL Introduction to Machine Learning Assignment 1 Answers 2022:- In This article, we have provided the answers of Introduction to Machine Learning Assignment 1.

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 IITKGP ASSIGNMENT 1 Answers 2022

• July 16, 2022 July 28, 2022

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

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

2. Which of the following is a not categorical feature? A. Gender of a person B. Height of a person C. Types of Mountains

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

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%

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

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

7. How many Boolean functions are possible with n features? A. (22) B. (2) C. (N²) D. (4)

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

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.

10. Identify whether the following statement is true or false? “Occam’s Razor is an example of Inductive Bias” A. True B. False

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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]

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Out of the Centre

Savvino-storozhevsky monastery and museum.

Zvenigorod's most famous sight is the Savvino-Storozhevsky Monastery, which was founded in 1398 by the monk Savva from the Troitse-Sergieva Lavra, at the invitation and with the support of Prince Yury Dmitrievich of Zvenigorod. Savva was later canonised as St Sabbas (Savva) of Storozhev. The monastery late flourished under the reign of Tsar Alexis, who chose the monastery as his family church and often went on pilgrimage there and made lots of donations to it. Most of the monastery’s buildings date from this time. The monastery is heavily fortified with thick walls and six towers, the most impressive of which is the Krasny Tower which also serves as the eastern entrance. The monastery was closed in 1918 and only reopened in 1995. In 1998 Patriarch Alexius II took part in a service to return the relics of St Sabbas to the monastery. Today the monastery has the status of a stauropegic monastery, which is second in status to a lavra. In addition to being a working monastery, it also holds the Zvenigorod Historical, Architectural and Art Museum.

Belfry and Neighbouring Churches

Located near the main entrance is the monastery's belfry which is perhaps the calling card of the monastery due to its uniqueness. It was built in the 1650s and the St Sergius of Radonezh’s Church was opened on the middle tier in the mid-17th century, although it was originally dedicated to the Trinity. The belfry's 35-tonne Great Bladgovestny Bell fell in 1941 and was only restored and returned in 2003. Attached to the belfry is a large refectory and the Transfiguration Church, both of which were built on the orders of Tsar Alexis in the 1650s.  

To the left of the belfry is another, smaller, refectory which is attached to the Trinity Gate-Church, which was also constructed in the 1650s on the orders of Tsar Alexis who made it his own family church. The church is elaborately decorated with colourful trims and underneath the archway is a beautiful 19th century fresco.

Nativity of Virgin Mary Cathedral

The Nativity of Virgin Mary Cathedral is the oldest building in the monastery and among the oldest buildings in the Moscow Region. It was built between 1404 and 1405 during the lifetime of St Sabbas and using the funds of Prince Yury of Zvenigorod. The white-stone cathedral is a standard four-pillar design with a single golden dome. After the death of St Sabbas he was interred in the cathedral and a new altar dedicated to him was added.

Under the reign of Tsar Alexis the cathedral was decorated with frescoes by Stepan Ryazanets, some of which remain today. Tsar Alexis also presented the cathedral with a five-tier iconostasis, the top row of icons have been preserved.

Tsaritsa's Chambers

The Nativity of Virgin Mary Cathedral is located between the Tsaritsa's Chambers of the left and the Palace of Tsar Alexis on the right. The Tsaritsa's Chambers were built in the mid-17th century for the wife of Tsar Alexey - Tsaritsa Maria Ilinichna Miloskavskaya. The design of the building is influenced by the ancient Russian architectural style. Is prettier than the Tsar's chambers opposite, being red in colour with elaborately decorated window frames and entrance.

At present the Tsaritsa's Chambers houses the Zvenigorod Historical, Architectural and Art Museum. Among its displays is an accurate recreation of the interior of a noble lady's chambers including furniture, decorations and a decorated tiled oven, and an exhibition on the history of Zvenigorod and the monastery.

Palace of Tsar Alexis

The Palace of Tsar Alexis was built in the 1650s and is now one of the best surviving examples of non-religious architecture of that era. It was built especially for Tsar Alexis who often visited the monastery on religious pilgrimages. Its most striking feature is its pretty row of nine chimney spouts which resemble towers.

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The Unique Burial of a Child of Early Scythian Time at the Cemetery of Saryg-Bulun (Tuva)

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Pages:  379-406

In 1988, the Tuvan Archaeological Expedition (led by M. E. Kilunovskaya and V. A. Semenov) discovered a unique burial of the early Iron Age at Saryg-Bulun in Central Tuva. There are two burial mounds of the Aldy-Bel culture dated by 7th century BC. Within the barrows, which adjoined one another, forming a figure-of-eight, there were discovered 7 burials, from which a representative collection of artifacts was recovered. Burial 5 was the most unique, it was found in a coffin made of a larch trunk, with a tightly closed lid. Due to the preservative properties of larch and lack of air access, the coffin contained a well-preserved mummy of a child with an accompanying set of grave goods. The interred individual retained the skin on his face and had a leather headdress painted with red pigment and a coat, sewn from jerboa fur. The coat was belted with a leather belt with bronze ornaments and buckles. Besides that, a leather quiver with arrows with the shafts decorated with painted ornaments, fully preserved battle pick and a bow were buried in the coffin. Unexpectedly, the full-genomic analysis, showed that the individual was female. This fact opens a new aspect in the study of the social history of the Scythian society and perhaps brings us back to the myth of the Amazons, discussed by Herodotus. Of course, this discovery is unique in its preservation for the Scythian culture of Tuva and requires careful study and conservation.

Keywords: Tuva, Early Iron Age, early Scythian period, Aldy-Bel culture, barrow, burial in the coffin, mummy, full genome sequencing, aDNA

Information about authors: Marina Kilunovskaya (Saint Petersburg, Russian Federation). Candidate of Historical Sciences. Institute for the History of Material Culture of the Russian Academy of Sciences. Dvortsovaya Emb., 18, Saint Petersburg, 191186, Russian Federation E-mail: [email protected] Vladimir Semenov (Saint Petersburg, Russian Federation). Candidate of Historical Sciences. Institute for the History of Material Culture of the Russian Academy of Sciences. Dvortsovaya Emb., 18, Saint Petersburg, 191186, Russian Federation E-mail: [email protected] Varvara Busova  (Moscow, Russian Federation).  (Saint Petersburg, Russian Federation). Institute for the History of Material Culture of the Russian Academy of Sciences.  Dvortsovaya Emb., 18, Saint Petersburg, 191186, Russian Federation E-mail:  [email protected] Kharis Mustafin  (Moscow, Russian Federation). Candidate of Technical Sciences. Moscow Institute of Physics and Technology.  Institutsky Lane, 9, Dolgoprudny, 141701, Moscow Oblast, Russian Federation E-mail:  [email protected] Irina Alborova  (Moscow, Russian Federation). Candidate of Biological Sciences. Moscow Institute of Physics and Technology.  Institutsky Lane, 9, Dolgoprudny, 141701, Moscow Oblast, Russian Federation E-mail:  [email protected] Alina Matzvai  (Moscow, Russian Federation). Moscow Institute of Physics and Technology.  Institutsky Lane, 9, Dolgoprudny, 141701, Moscow Oblast, Russian Federation E-mail:  [email protected]

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