What type of prerequisite required to cover this topic😢
@lidiyapriyadarsinik2815Ай бұрын
Who can give a thumbs down to this lecture is beyond my understanding
@ILoveHills-fq6boАй бұрын
DO NOT ENROLL IN THIS COURSE. I have taken this course and has cleared its exam under ELITE certificate. I am sharing mine and my friends experience regarding this course from Jan-April 2024. This is an VERY INTENSE MATHEMATICAL course and no where close to introduction to ML. If you want to make a simple subject very tough then study from this professor. This course is taught with worse teaching and explaining techniques. The faculty (an IIT professor) teaches with chalk and paper. Nil use of slides. He comes with the formulas noted on a sheet and will just vomit them out on the green board without any background explanations. He does not use any examples/numericals to clear the concepts during the lectures. Coming on the assignment part, they are very tough, tricky and very less related to the things taught in the class. The NPTEL exam will be full of mathematics and statistics related numerical questions which are not at all taught during the lectures. RESULT=1198 (PASSED)/8308(TOTAL ENROLLED)=14% (approx) YOU CAN YOURSELF CHECK THAT INITIAL LECTURES IN THE PLAYLIST HAVE LAKHS OF VIEWS and then views fall drastically to LESS THAN 10 THOUSAND. We have studied from CAMPUSX, KRISH NAYAK AND Dr. MAHESH HUDDAR on youtube to pass this subject.
@ILoveHills-fq6boАй бұрын
DO NOT ENROLL IN THIS COURSE. I have taken this course and has cleared its exam under ELITE certificate. I am sharing mine and my friends experience regarding this course from Jan-April 2024. This is an VERY INTENSE MATHEMATICAL course and no where close to introduction to ML. If you want to make a simple subject very tough then study from this professor. This course is taught with worse teaching and explaining techniques. The faculty (an IIT professor) teaches with chalk and paper. Nil use of slides. He comes with the formulas noted on a sheet and will just vomit them out on the green board without any background explanations. He does not use any examples/numericals to clear the concepts during the lectures. Coming on the assignment part, they are very tough, tricky and very less related to the things taught in the class. The NPTEL exam will be full of mathematics and statistics related numerical questions which are not at all taught during the lectures. RESULT=1198 (PASSED)/8308(TOTAL ENROLLED)=14% (approx) YOU CAN YOURSELF CHECK THAT INITIAL LECTURES IN THE PLAYLIST HAVE LAKHS OF VIEWS and then views fall drastically to LESS THAN 10 THOUSAND. We have studied from CAMPUSX, KRISH NAYAK AND Dr. MAHESH HUDDAR on youtube to pass this subject.
@darkseid856Ай бұрын
For anyone confused from 10:50 onwards, he is basically doing what is called *Gram-Schmidt Orthogonalization process* . Basically the idea is , {1,x1,x2,....,xP) where each element in this set is N dimensional vector. This acts as a basis for the vector space spanned by these vectors , however these may or may not be orthogonal. So using the Orthogonalization process we first create a new set of basis vectors (1,z1,z2,z3,....,zP} such that all these vectors are orthogonal to each other. Once we have created this new orthogonal set , we just do the simple univariate regression as we have been doing before but on this new orthogonal set of basis vectors. And in the end of this process we get the beta coefficient.
@sakshimishra64502 ай бұрын
done
@RahulYadav-rl4cd2 ай бұрын
moo ku na pta bhai
@adityasiwach24002 ай бұрын
Kah kehro
@deswalsabh9712 ай бұрын
kaahe na pto muu ko bhi naa pto bhivani jaa k dekh kaa karr roo hai
@deswalsabh9712 ай бұрын
@@adityasiwach2400 muu ko naa pto tu kaa kah roo h
@studyonly-do1ct2 ай бұрын
bhai pto to krno pdega
@krishnabillonaire5162 ай бұрын
this course is too old
@megaforce48703 ай бұрын
Time waste
@sripradhaiyengar99803 ай бұрын
Thank you
@mondeepxrma78943 ай бұрын
I think because of this course i m not going to get my degree😮
@dailyentertainment8443 ай бұрын
no 1 chuthiya professor award goes to him (thevidi punda )
@coderide4 ай бұрын
Nice lecture
@contectkumar1124 ай бұрын
Ye teacher hai kya ....bc kya hi pdha rha hai
@avinashtiwari77434 ай бұрын
He taught Perplexity CEO
@ece43pranjalrai624 ай бұрын
the only problem with nptel i always wonder that why they don't share the ppt!!
@manudasmd4 ай бұрын
Forward stage wise selection is computationally expensive than step wise selection right ? is there a mistake ?
@30saransh4 ай бұрын
People who are finding this lecture hard, remember this is a recap and if you don't know the concept you will not understand it. For learning Linear algebra you can refer following resources: 1. 3Blue1Brown LA playlist, its short sweet and visual. Enough for this course but not to underatand LA in full depth. 2. MIT 18.06 lectures By Prof. Gilbert Strand, its long but very thorough and fun to understand.
@manudasmd4 ай бұрын
2:40 lol :D
@manudasmd4 ай бұрын
So basically the lecture covers orthogonalising non orthogonal basis by regressing one basis onto other and then finding the residual and use the residual vector instead of the first vector to regress output vector. LOL .
@killergenix4 ай бұрын
poor teaching
@appukkuttan0194 ай бұрын
If you discussed some problems, maybe then students might understand how to work out questions related to these THERE'S BASICALLY NO SOLVED EXAMPLES! and the students are to find out how to solve questions themselves
@kramprabhu5 ай бұрын
Seems this guy is not interested in teaching. He keeps reading from a written text. No life in his speach.
@sidd_borah5 ай бұрын
Please suggest an easy-to understand book for probability theory.
Werid context to use the word chaffing but alright, let's go!
@jhaaditya77647 ай бұрын
Thank you sir
@solitaryreaper13637 ай бұрын
Thank you sir for sharing it with us.
@user-qu9vj2zm5n8 ай бұрын
What book should I have to refer..
@niydable8 ай бұрын
Legit thought my headphone was faulty because audio is only coming from the left side
@vaibhavagarwal90558 ай бұрын
Worst Explanation he starts and teaches as if students know everything doesnt teaches basic concepts only high level mathematics without explaining basic concepts
@leojoy93477 ай бұрын
This is not a bad explanation. You can take any lectures in stanford or cornell you would the same level of teaching. The problem is that you need a good knowledge on linear algebra and statistics to understand this. Else you wouldn't understand the calculations at all.
@RAUSHANKUMARME-vt5pz8 ай бұрын
very informatic sir
@n.kranjan15739 ай бұрын
oho….lots of math😳😳😳
@yugandharkanaparthi18259 ай бұрын
sir please share the notes regarding to machine learning course
@jjjyotish9 ай бұрын
The last part of the lecture should be actually LinearMMSE instead of Least squares soln since we are looking at "Expected" error.
@ravikillar537410 ай бұрын
very very very very very very bad teacher all over world
@Lucky-vm9dv10 ай бұрын
Is python really necessary to learn machine learning
@user-vf3jk2df1o10 ай бұрын
not recommendable course
@sg703110 ай бұрын
8:36 - 8:42 🤣🤣 turned around expecting some nods but everyone's looking lost in the woods
@theb10studios4710 ай бұрын
Orumaathiri matedta paruvaadi aayi poi
@chordiasankalp82010 ай бұрын
Absolutely dull lecturer
@chordiasankalp82010 ай бұрын
The teacher should teach with passion duh
@chordiasankalp82010 ай бұрын
The instructors voice is full of depression
@vinaygohel821611 ай бұрын
3:22 Did I really hear the voice of turning new page😂
Пікірлер
Super 💯❤
Done 👍❤
What type of prerequisite required to cover this topic😢
Who can give a thumbs down to this lecture is beyond my understanding
DO NOT ENROLL IN THIS COURSE. I have taken this course and has cleared its exam under ELITE certificate. I am sharing mine and my friends experience regarding this course from Jan-April 2024. This is an VERY INTENSE MATHEMATICAL course and no where close to introduction to ML. If you want to make a simple subject very tough then study from this professor. This course is taught with worse teaching and explaining techniques. The faculty (an IIT professor) teaches with chalk and paper. Nil use of slides. He comes with the formulas noted on a sheet and will just vomit them out on the green board without any background explanations. He does not use any examples/numericals to clear the concepts during the lectures. Coming on the assignment part, they are very tough, tricky and very less related to the things taught in the class. The NPTEL exam will be full of mathematics and statistics related numerical questions which are not at all taught during the lectures. RESULT=1198 (PASSED)/8308(TOTAL ENROLLED)=14% (approx) YOU CAN YOURSELF CHECK THAT INITIAL LECTURES IN THE PLAYLIST HAVE LAKHS OF VIEWS and then views fall drastically to LESS THAN 10 THOUSAND. We have studied from CAMPUSX, KRISH NAYAK AND Dr. MAHESH HUDDAR on youtube to pass this subject.
DO NOT ENROLL IN THIS COURSE. I have taken this course and has cleared its exam under ELITE certificate. I am sharing mine and my friends experience regarding this course from Jan-April 2024. This is an VERY INTENSE MATHEMATICAL course and no where close to introduction to ML. If you want to make a simple subject very tough then study from this professor. This course is taught with worse teaching and explaining techniques. The faculty (an IIT professor) teaches with chalk and paper. Nil use of slides. He comes with the formulas noted on a sheet and will just vomit them out on the green board without any background explanations. He does not use any examples/numericals to clear the concepts during the lectures. Coming on the assignment part, they are very tough, tricky and very less related to the things taught in the class. The NPTEL exam will be full of mathematics and statistics related numerical questions which are not at all taught during the lectures. RESULT=1198 (PASSED)/8308(TOTAL ENROLLED)=14% (approx) YOU CAN YOURSELF CHECK THAT INITIAL LECTURES IN THE PLAYLIST HAVE LAKHS OF VIEWS and then views fall drastically to LESS THAN 10 THOUSAND. We have studied from CAMPUSX, KRISH NAYAK AND Dr. MAHESH HUDDAR on youtube to pass this subject.
For anyone confused from 10:50 onwards, he is basically doing what is called *Gram-Schmidt Orthogonalization process* . Basically the idea is , {1,x1,x2,....,xP) where each element in this set is N dimensional vector. This acts as a basis for the vector space spanned by these vectors , however these may or may not be orthogonal. So using the Orthogonalization process we first create a new set of basis vectors (1,z1,z2,z3,....,zP} such that all these vectors are orthogonal to each other. Once we have created this new orthogonal set , we just do the simple univariate regression as we have been doing before but on this new orthogonal set of basis vectors. And in the end of this process we get the beta coefficient.
done
moo ku na pta bhai
Kah kehro
kaahe na pto muu ko bhi naa pto bhivani jaa k dekh kaa karr roo hai
@@adityasiwach2400 muu ko naa pto tu kaa kah roo h
bhai pto to krno pdega
this course is too old
Time waste
Thank you
I think because of this course i m not going to get my degree😮
no 1 chuthiya professor award goes to him (thevidi punda )
Nice lecture
Ye teacher hai kya ....bc kya hi pdha rha hai
He taught Perplexity CEO
the only problem with nptel i always wonder that why they don't share the ppt!!
Forward stage wise selection is computationally expensive than step wise selection right ? is there a mistake ?
People who are finding this lecture hard, remember this is a recap and if you don't know the concept you will not understand it. For learning Linear algebra you can refer following resources: 1. 3Blue1Brown LA playlist, its short sweet and visual. Enough for this course but not to underatand LA in full depth. 2. MIT 18.06 lectures By Prof. Gilbert Strand, its long but very thorough and fun to understand.
2:40 lol :D
So basically the lecture covers orthogonalising non orthogonal basis by regressing one basis onto other and then finding the residual and use the residual vector instead of the first vector to regress output vector. LOL .
poor teaching
If you discussed some problems, maybe then students might understand how to work out questions related to these THERE'S BASICALLY NO SOLVED EXAMPLES! and the students are to find out how to solve questions themselves
Seems this guy is not interested in teaching. He keeps reading from a written text. No life in his speach.
Please suggest an easy-to understand book for probability theory.
Nice overview of probability 🤷♀
worst lecture. irritating background noise. 1000 rupess waste.
i know how to read the slides
Bad video quality
Werid context to use the word chaffing but alright, let's go!
Thank you sir
Thank you sir for sharing it with us.
What book should I have to refer..
Legit thought my headphone was faulty because audio is only coming from the left side
Worst Explanation he starts and teaches as if students know everything doesnt teaches basic concepts only high level mathematics without explaining basic concepts
This is not a bad explanation. You can take any lectures in stanford or cornell you would the same level of teaching. The problem is that you need a good knowledge on linear algebra and statistics to understand this. Else you wouldn't understand the calculations at all.
very informatic sir
oho….lots of math😳😳😳
sir please share the notes regarding to machine learning course
The last part of the lecture should be actually LinearMMSE instead of Least squares soln since we are looking at "Expected" error.
very very very very very very bad teacher all over world
Is python really necessary to learn machine learning
not recommendable course
8:36 - 8:42 🤣🤣 turned around expecting some nods but everyone's looking lost in the woods
Orumaathiri matedta paruvaadi aayi poi
Absolutely dull lecturer
The teacher should teach with passion duh
The instructors voice is full of depression
3:22 Did I really hear the voice of turning new page😂
Thank you sir