16. Learning: Support Vector Machines

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MIT OpenCourseWare

MIT OpenCourseWare

10 років тому

MIT 6.034 Artificial Intelligence, Fall 2010
View the complete course: ocw.mit.edu/6-034F10
Instructor: Patrick Winston
In this lecture, we explore support vector machines in some mathematical detail. We use Lagrange multipliers to maximize the width of the street given certain constraints. If needed, we transform vectors into another space, using a kernel function.
License: Creative Commons BY-NC-SA
More information at ocw.mit.edu/terms
More courses at ocw.mit.edu

КОМЕНТАРІ: 982
@alaaeltayeb5794
@alaaeltayeb5794 4 роки тому
Prof Patrick Winston has sadly passed away on July 19, 2019 rest in peace , the knowledge you’ve passed to thousand of students is your legacy and its forever thank you
@sandorszabo2470
@sandorszabo2470 4 роки тому
Very bad news :-(( RIP.
@haggar11
@haggar11 4 роки тому
A real loss Prof Patrick Winston has dedicated himself to give knowledge on AI.
@nikaporozov
@nikaporozov 4 роки тому
Very sad news RIP prof ;(
@DeepakKumar-uz4xy
@DeepakKumar-uz4xy 4 роки тому
Oh damn...RIP
@SuperIronwire
@SuperIronwire 4 роки тому
Rest in peace!
@afarehdokht1992
@afarehdokht1992 3 роки тому
I’m jealous of every single student in this class. And thank god i am alive and can watch this on youtube.
@romanemul1
@romanemul1 3 роки тому
why jealous ?
@storytel3000
@storytel3000 3 роки тому
@@romanemul1 coz he can't use the bathrooms there.
@jjpp1993
@jjpp1993 3 роки тому
@@romanemul1 of a world class education
@cratermoney6941
@cratermoney6941 2 роки тому
I wouldn’t be jealous at all, you’re getting the same education for FREE
@asfasdfsd8476
@asfasdfsd8476 Рік тому
Don't be jealous of any initial condition. In the end it won't matter. You will get there if you are resourceful person anyway, and if you aren't such a person then no initial condition going to help.
@sansin-dev
@sansin-dev 4 роки тому
Tremendous respect for any professor who writes out the entire math on board and does not use notes to do so.
@pranavtagore
@pranavtagore Рік тому
my fluid mechanics professor wasn't that good. she would use books and notes throughout her lecture to write the equations on the board. however, she had a good way of teaching that made everything understandable.
@user-ip9bm4mz1v
@user-ip9bm4mz1v Рік тому
31:39 Why do I need to find the maximum value of the L value? I was looking for the minimum value of 1/2 * |W|^2, but I don't understand why you're looking for the maximum value of L as you move on to L.
@pulipakasrikiran9307
@pulipakasrikiran9307 Рік тому
@@user-ip9bm4mz1v1/2w2 has a constraint so you use a lagrengian multiplier alphai multiplied with the constraint and add it to the intial equation.You treat this L as a new minimizing solution to minimize the original equation with the constraint.
@ChibuRawk
@ChibuRawk 7 місяців тому
​@@pranavtagoredid you really compared fluid mechanics equations to this basic linear sh*t? No, seriously?
@gregmcmahan7420
@gregmcmahan7420 Місяць тому
​@@ChibuRawkNot sure why you have to be a jerk.
@realisticlevel2553
@realisticlevel2553 9 місяців тому
I've been watching a lot of MIT, Stanford, Harvard, Princeton lectures, but this... This was phenomenal, hands down the best lecture I've ever seen. Rest in Peace Prof
@aneekdas3056
@aneekdas3056 3 роки тому
Feel blessed to have attended his lectures live and work under his supervision. Rest in peace Prof. You will always be an inspiration to me.
@joshrichardson4527
@joshrichardson4527 Рік тому
I love gun soooo much
@chrism3790
@chrism3790 5 років тому
I just came from Andrew Ng's ML course in order to understand SVMs better. I found something quite interesting. Andrew gets the optimization criterion at 21:49 from an altogether different place. He arrives at SVMs by modifying the logistic regression's cost function, and the optimization criterion emerges from the regularization portion of the cost function. He then explains why that leads to a maximum margin. In contrast, this professor starts by obtaining the margin width algebraically with the intention of maximizing it, and then explains why that leads to separating data. Pretty cool.
@astropiu4753
@astropiu4753 5 років тому
Same here. Now I'm trying to interrelate the parameters of the two approaches.
@-long-
@-long- 4 роки тому
lol same here, cheers. Great course from Prof. Andrew too but I couldn't understand everything so I was looking for alternative lecture
@rogerioluizsi
@rogerioluizsi 4 роки тому
Same here!
@ritayanganguly7786
@ritayanganguly7786 4 роки тому
I'd argue this approach is working better for me.
@fruitbaskets7984
@fruitbaskets7984 4 роки тому
Which course are you taking? Thanks in advance!
@homataha5626
@homataha5626 4 роки тому
RIP ! Prof Winston!!! you inspired lots of ppl!
@tobiasksr23
@tobiasksr23 4 роки тому
:(
@TomOtero1984
@TomOtero1984 4 роки тому
:(
@teenspirit1
@teenspirit1 4 роки тому
He dead? That's very sad. He seemed like a nice fellow.
@Mutual_Information
@Mutual_Information Рік тому
MIT offering free courses on UKposts in the early moves is the ultimate education move. I respect it.
@bunt7243
@bunt7243 8 років тому
This is why MIT is MIT. Good work Prof and Thank you to the team. We hope to see more lectures related to Machine learning and Data science from MIT.
@immcguyver07
@immcguyver07 7 років тому
pushpender pareek, yes. for about $50,000, they will give you access to a year's worth of additional lectures.
@lobtyu
@lobtyu 7 років тому
+immcguyver07 Don't forget the ability to work with or for top researchers, the exposure you get to other amazing students with a wide variety of programming backgrounds, the clubs you can join to collaborate with these other students, being part of a pipeline that regularly sends people to silicon valley which allows them to pay off student debt within a few years, or being part of a pipeline that regularly sends people to top grad schools which is the only way to get a job in academia.
@valken666
@valken666 6 років тому
He's always out of breath, as if about to die. That's very annoying to me. lobtyu - Just read the papers, you'll be a much better researcher and for free.
@mpm3363
@mpm3363 4 роки тому
The historical part of Vapnik’s story is very inspiring.
@mikejohnstonbob935
@mikejohnstonbob935 7 років тому
damn! this instructor's lines are so damn crisp!
@mcgil8891
@mcgil8891 5 років тому
mike johnston Bob ikr
@mayurkulkarni755
@mayurkulkarni755 8 років тому
Best explanation of SVM on internet !
@TheMix2ra
@TheMix2ra 6 років тому
It is good!!! , I found a better one: ukposts.info/have/v-deo/i3hzeqFojIJ_zXk.html
@omgcoin
@omgcoin 5 років тому
Professor if you ever read this, THANK YOU. I was actually sad the lecture ended eventually. The world needs more teaching like yours.
@scikick
@scikick 5 років тому
Machine learning is one of the worst taught classes in schools today - lecturers who are too into implementations and don't understand the basics well enough themselves, don't have motivation to teach well, and overcrowded classes because everyone wants to be a data scientist.. Thank you MIT for releasing this gem into the public domain for millions to watch.. This was easily one of the best SVM lectures ever!!
@mitocw
@mitocw 5 років тому
Ackchyually... this is under a Creative Commons License (NC-BY-SA) and not in the Public Domain ...but we are glad you enjoyed it! =D
@slavrine
@slavrine 5 років тому
I wish my math prof had his sense of humor and conciseness! Maby I would be doing my math PhD now instead of coding
@axscs1178
@axscs1178 Рік тому
This is how things should always be taught. Patience, deep understanding and passion to teach. I wish I would've had a professor like him as a graduate student.
@nagamallika1982
@nagamallika1982 9 років тому
One of the best lectures I ever heard-methodical & extremely helpful!Thank you.I will definitely come back for more - appreciate this.
@BharathRamachandraiah
@BharathRamachandraiah 4 роки тому
10:23 the way he interacts with the student. so nice.
@mohamedgamal-gi5ws
@mohamedgamal-gi5ws 2 роки тому
RIP Prof Patrick this lecture is gold , Never saw anyone explain all the tiny details this smooth in less than an hour
@saitejabobby9990
@saitejabobby9990 4 роки тому
That story about how SVM evolved gave me loadz of motivation. Great ideas always takes some gap and then immortalizes.
@ritikjain4811
@ritikjain4811 4 роки тому
Simply loved it! Don't have any words for the professor who taught the sophisticated concepts with such simplicity...
@headeeg
@headeeg 3 роки тому
I am grateful that I was given the opportunity to participate in this lesson. I really put a lot of thought into getting the double problem of SVM really into my head. Prof. Patrick Winston was the one who made it click for me. It is sad to read in the comments that we lost a great teacher who helped to make the world a smarter place.
@ahmedwesam7286
@ahmedwesam7286 4 місяці тому
You are lucky my friend, i wish if i could.
@Cyphlix
@Cyphlix 10 років тому
One of the best lectures I've seen, so concise and easy to follow :D
@balachandar2012
@balachandar2012 4 роки тому
Helped me with my Statistical Machine Learning class. Thank you Professor. RIP
@shauryasharma2865
@shauryasharma2865 4 роки тому
BRILLIANT. Massive respect for the knowledge and simplicity of the professor here.
@algebra5766
@algebra5766 8 років тому
This is a brilliant lecture!
@henokgebeyehu1507
@henokgebeyehu1507 4 роки тому
The power of the rewind button in learning is actually phenomenal!
@shashankaich7632
@shashankaich7632 4 роки тому
One of the best videos on SVM, which also explains the Kernalization so well.
@DivineAbhi
@DivineAbhi 8 років тому
Perfect explanation. so much better than anything else online
@akshatchhaya6121
@akshatchhaya6121 2 роки тому
What a gem of an lecture, Trying to understand equations directly just makes you mug up somethings and like you never understand it fully. What I found is that when you actually run yourself through a simulation of what the inventor of the equation did and follow the footsteps than things start making sense eventually and you arrive at solution and you think huh that wasn't to hard. Rest in Peace Prof Patrick Winston world needs more professors like you really man. This is first video lecture of his I am watching and I can feel what a great man we lost!!
@pedroveloso62
@pedroveloso62 7 років тому
Really nice class. This professor managed to go through some tricky topics maintaining the simplicity and coherence of his argument.
@bobeatschocolate
@bobeatschocolate 7 років тому
This professor is very, very well spoken when it comes to explaining SVM's. Clear, concise, focused on one instance of one issue at a time... Many professors try to show you the entirety of the math while walking you through the conceptual ideas and it makes SVM's very difficult to learn! This man is quite the opposite! Great work! (And by math I didn't mean just showing the margins, graphs etc.. meant proof of the equations which two of my professors did in two separate machine learning/data science classes.)
@nuraddeenb
@nuraddeenb 10 років тому
MAN, that was good!! probably the best introduction to SVM available online.
@juliogodel
@juliogodel 7 років тому
For the record..Ive started watching one lecture and now I am watching the whole course...Patrick Winston is a marvellous teacher and I wish to watch *everything* this guy has to teach. Are there any other courses he teaches? If so, please record and put them online!
@putuaditya3741
@putuaditya3741 7 років тому
Fortunately, I found this video before my thesis defense tomorrow. Thank you so much, Prof. Patrick Winston. Keep up!
@amarparajuli692
@amarparajuli692 4 роки тому
What a beautiful lecture. Thank you, Prof. RIP Prof Patrick Winston.
@solomonleo3025
@solomonleo3025 3 роки тому
12:40 , that guy just saved me from suicide, I was like, "wtf, where did that w vector disappear!!" 😂😂😅😅
@amitgp2007
@amitgp2007 3 роки тому
Me too......
@phuthangmaponopono1015
@phuthangmaponopono1015 2 роки тому
Same here lol
@OttoFazzl
@OttoFazzl 7 років тому
This lecture by Patrick Winston is simply amazing! His way of teaching is one of the most insightful approaches to highly technical subjects that I have ever encountered. I am so grateful to MIT for letting students all over the world to learn from such people as him. The lecture on boosting is also very good.
@jeswinaugustine5384
@jeswinaugustine5384 5 років тому
After going through many articles and online courses, i still didn't understood the idea of SVM clearly. This one is surely the best video on SVM available online. Thanks a lot professor.
@mohammadashrafulislam7521
@mohammadashrafulislam7521 3 роки тому
Best lecture on SVM I have seen so far...Just loved the way he explained the concept and the functions! Gosh if I could just attend his lectures face to face
@MrPrince750
@MrPrince750 4 роки тому
RIP Patrick!!!It is sad you are no longer with us. You are a great teacher..
@faizanbeg7356
@faizanbeg7356 4 роки тому
RIP Professor, the world needs more people like you.
@jamespatrick5348
@jamespatrick5348 6 років тому
Excellent presentation that catches the subtle nuances of SVM and the thought processes that went into its creation. Fabulous!
@gutlesswarrior
@gutlesswarrior 8 років тому
When more than half the comments are along the lines of "best SVM explanation I've seen", you know you've stumbled upon a gem of a lecture. Great work, I'll be checking out as many of your other lectures as I can because of this.
@asinegaasinega
@asinegaasinega 3 роки тому
what do you expect? this is the difference between going to MIT and going everywhere else. It's not the knowledge that's the difference. It's how the teachers are able to relate the material in a very palatable fashion, that's the difference. I sometimes rue in my old age what I missed (because I didn't go to a good school) because i see the difference in my own understanding of things compared to those that went to good schools. It's not that I am not capable of understanding. It's that they have an in-depth grasp of the material because they sat under the tutilage of people like this professor. That's the difference between MIT and coursera or any other school folks.
@Iamfafafel
@Iamfafafel 5 місяців тому
it's annoying
@Saravananmicrosoft
@Saravananmicrosoft 4 роки тому
Amazing lecture, i watched almost 3 times back to back, its always gives you always refreshing thoughts. My honour to see this lecture thanks prof, still teaching so many students like me. You are simply great.
@judedavis92
@judedavis92 Рік тому
"If you can't explain it simply, you don't understand it well enough." ~ Einstein Professor Winston clearly understands the topics he teaches.
@sankopanza
@sankopanza 8 років тому
The best explanation of SVM I have come across. Hats off to Prof Patrick.
@mohankrishna7979
@mohankrishna7979 4 роки тому
Excellent explanation of SVM. Awesome job by the professor. clear, concise and has a story flow
@eVul6
@eVul6 6 років тому
I was watching the video and thinking "Wow, the pace of the lectures at MIT is pretty fast. These students must be really bright to follow the professor. No wonder that I'm not studying there". At the end, I found that, unbeknownst to me, I was watching it all along at the 1.25 speed.
@mcgil8891
@mcgil8891 5 років тому
eVul6 OMG... Thank you!! I just realized I was watching it at 1.5x
@Ash-cc1uj
@Ash-cc1uj 5 років тому
i did the exact same thing
@da_lime
@da_lime 5 років тому
I am watching it with normal speed, I guess I need to set it on 0.5
@michaelmarcic9636
@michaelmarcic9636 5 років тому
Thanx for the commend. I watched it on normal speed, but thought that this guy is very slow, so I put it on 1.25. now it's fine.
@veerpal5913
@veerpal5913 5 років тому
eVul6 donkey
@Sumit-dn6ls
@Sumit-dn6ls 9 років тому
Excellent! Simple explanation right down to the basics.
@MsVanessasimoes
@MsVanessasimoes 3 роки тому
I am very thankful for all people that worked to bring this amazing lecture from Prof. Patrick Winston to people around the world.
@andreidumitrache2077
@andreidumitrache2077 10 років тому
Perfectly presented and explained. The best lecture on SVMs I've seen.
@robertchen6104
@robertchen6104 5 років тому
Like all students everywhere, I was watching this lecture and thinking, "if only I had had a teacher like Prof. Winston when I started in physics, I would have ...." Or at least, I would have had an easier time in all my other courses, and later in doing research, or just learning new things, like modern machine learning.
@sarkercuisine8693
@sarkercuisine8693 5 років тому
Wow. Best lecture for SVM I ever watched. Thanks a lot, MIT OpenCourseWare and Patrick Winston.
@gmarciani
@gmarciani 7 років тому
The best lesson on SVM that I've ever heard! Thanks for sharing!
@allisswellable
@allisswellable 5 років тому
This is one of the best explanation of SVM i have ever seen. This professor made this complex concept so easy to understand. KUDOS to him!!
@yuriaurelio810
@yuriaurelio810 7 років тому
Wow. This guys is the best teaching SVM.
@nkundukozerajanvier162
@nkundukozerajanvier162 6 років тому
Amazing lecture. Thank you and MIT in general. we love your priceless support to global education
@hahablahblaah
@hahablahblaah 9 років тому
This is an incredibly interesting lecture! Had to watch it twice and do some back and forth to fully understand, but really well explained!
@jacobgonzalez731
@jacobgonzalez731 7 років тому
Best SVM lecture I have seen. This professor does a great job of teaching the concept of SVM and the thought process behind it.
@CKPSchoolOfPhysics
@CKPSchoolOfPhysics 2 роки тому
This single video is much more powerful than all videos available on youtube about SVM. so, lucky to found his lecture. Simplicity of teaching at its best. Love you prof. RIP.
@meghnanatraj3360
@meghnanatraj3360 8 років тому
The best SVM lecture ever! Thank you soooooo much!!!!
@amineech-cherif2386
@amineech-cherif2386 7 років тому
Do you understand all of it ??!
@hunir1
@hunir1 7 років тому
I understand all of it in-fact this is really a basic intro, you shouldn't have a problem with this. If you do I suggest pausing the video at each stage and clear up on points that you feel you have understood. It has only been algebra and calculus.
@amineech-cherif2386
@amineech-cherif2386 7 років тому
I agree that this intro is very easy to follow, but it is too abstract I think. Like for instance the mathematical conveniences, for example when we divide the W by 1/2 is not clear. Also, a thorough understanding of quadratic programming is needed to fathom the optimization part of the SVM. Simply put, this lecture does not cover the entirety of SVM.
@meghnanatraj3360
@meghnanatraj3360 7 років тому
I guess it depends on how much you know initially. (beginner to advanced). This caters to the middle. Who have know some basic ML math and yet are new to ML concepts! Like me! :) So i guess its just perspective and he cannot cater to everyone in the audience! And no, I didn't understand every bit of it. ^_^
@amineech-cherif2386
@amineech-cherif2386 7 років тому
Exactly. In my case, I had to study some of the basics of Calculus 2, like the Lagrangian, as in my computer science dept we don't study it.
@georgedikos1424
@georgedikos1424 5 місяців тому
one of the most inspirational lectures ever. Gave me the same energy and motivation like my first courses at Engineering school trying to bring together Finite Element Methods, approximation theory and functional analysis and the code in machine language or fortran.
@BrandonRohrer
@BrandonRohrer 6 років тому
Excellent explanation Professor Winston. You have the rare skill of explaining both the math and its motivation clearly to a novice audience.
@alalize
@alalize 9 років тому
The Caltech prof' Yaser Mofasa explained it another way (more mathy), but this is clearer.
@billwindsor4224
@billwindsor4224 4 роки тому
Wow, that is an excellent lecture on SVM, thank you! Hang in there until the "miracle" part that starts at 43:30; then he shows the transformations that make SVM amazing.
@spvimal
@spvimal 2 роки тому
He did the miracle of teaching things which others struggle with for 3+ hours. Wow, what a class? Miss you Professor. We needed lot more classes from you and all of them are in youtube ;)
@johnq4841
@johnq4841 4 роки тому
best svm class i have ever had, really solve my math concerns
@junecnol79
@junecnol79 5 років тому
i watched several times back and forth, finally, i THINK i understand
@tgowda
@tgowda 7 років тому
great lecture! Thanks MIT OCW
@jorgejgleandro
@jorgejgleandro 5 років тому
Cristal clear explanation! A good professor is like this: a bridge (instead of a wall) between the student and the matter. Congratz!
@yuwang6841
@yuwang6841 8 років тому
professor is good ,the formula goes step by step ,very clear ,it's wonderful to watch this lecture with the paper:A tutorial on support vector machine for pattern recognition!
@yassineouali1888
@yassineouali1888 4 роки тому
What a professor, may he rest in peace
@kellyli1920
@kellyli1920 9 років тому
best explaination! I saw many materials that is very hard to understand!
@sleyking514
@sleyking514 4 роки тому
hello
@VikasKM
@VikasKM 3 роки тому
This is by far the best lecture on support vector machine. just amazing lecture- a must watch
@mrodek
@mrodek 6 місяців тому
This is an absolutely amazing lecture. Soo much goodness and wisdom. RIP Prof. and thank you.
@sridharaddagatla
@sridharaddagatla 4 роки тому
amazing explanation !!! Most other tutors skip the algebra part which makes learning SVM a black box but this delineated explanation of prof patrick is amazingly simple and thorough. Thanks Prof patrick and MIT opencourseware.
@krakenmetzger
@krakenmetzger 4 роки тому
Note for myself and others: the reason in English why (dL / dw)[(1/2) |w|^2] = w is because dL/dw is a directional derivative. Equivalently, we are rotating the coordinate system such that the w direction is an axis, and taking the partial derivative with respect to w. We can now treat |w|^2 just like x^2 if we're doing normal calculus, particularly because |x|^2 = x^2 for all x.
@jagannathan1014
@jagannathan1014 Рік тому
Thanks a lot man i was confused but went on with the lecture since i didnt want to get distracted, i went in the comments anyway and saw this within a single scroll , You dropped this: 👑
@anushka.narsima
@anushka.narsima Рік тому
omg thank you so much, I've been looking around for the past few days to get past that step
@Iamfafafel
@Iamfafafel 5 місяців тому
i guess dL/dw means consider the vector of partials (dL/dw^1,...,dL/dw^n) where w=(w^1,...,w^n). i can't really make sense of your comment
@antonylawler3423
@antonylawler3423 7 років тому
Thought I would add to the voices of approval. I've just completed an elementary Machine Learning course (SVM wasn't on it), and have watched quite a few youtube videos, including those from Andrew Ng. The clarity of language, display, sequence of demonstration and speed of this lesson are absolutely spot on. Thanks !
@alexanderkurz2409
@alexanderkurz2409 6 місяців тому
One of my favourite math lectures on the internet. I probably wrote the same comment some years ago, but here I go again. Thanks to Professor Winston and everybody else who made this available. I do teach math myself and I deeply admire how he boils it down to the essentials without leaving anything important out. Just looking at how little there is on each board and how clearly the beauty of the subject shines through ... a true master class. And I always thought we should teach more math history, so it is great to hear from him how the ideas actually developed.
@junzhemiao7118
@junzhemiao7118 8 років тому
Best explanation I have seen so far. Much better than Andrew Ng in my opinion.
@mmattb
@mmattb 5 місяців тому
That is the best chalk I've ever seen.
@nkdms.2031
@nkdms.2031 6 років тому
The "widest street approach" ... oh man! Perhaps the only lecturer that can throw "gems" like that + the story at the end... In three words he explained everything!
@modusponensthethird
@modusponensthethird 2 роки тому
i have an exam tommorow in india and Prof Patrick teached me what my indian प्रोफ़ेसर couldnt teach me in a whole semester. You sir saved my life...
@ChadieRahimian
@ChadieRahimian 7 років тому
A combination of this lecture with a 10min lecture on SVMs by Victor Lavrenko worked amazing for me!
@OttoFazzl
@OttoFazzl 7 років тому
I went to that video and found it really useful, thanks for sharing.
@venkateshsv7434
@venkateshsv7434 7 років тому
Shadi Rahimian .. I really don't know what is this.. :-( I. very basic
@alifawzi4566
@alifawzi4566 7 років тому
thank you shadi itis god advise for victor video
@abdullahalsaidi6009
@abdullahalsaidi6009 6 років тому
Thanks alot , his video was very useful
@saliheenafridi9116
@saliheenafridi9116 4 роки тому
Thanks for telling us
@cheeloongsoon9090
@cheeloongsoon9090 5 років тому
For everyone watching, note that there is a mistake on the board. At 19:20 , a student asked a correct clarification. w dot xPlus should be (1-b) , whereas w dot xMinus should be (-1-b), then you can get the 2/norm(w) equation.
@sajay96
@sajay96 2 роки тому
It's written as 1+b because negative value of w dot xMinus is considered, so not a mistake.
@cheeloongsoon9090
@cheeloongsoon9090 2 роки тому
@@sajay96 I guess he corrected it at 19:53
@flxblyyk
@flxblyyk 3 роки тому
This is the best SVM lecture I have ever heard! Everything is so well explained, so that it helped my ambiguous understanding to be clear. Thanks a lot for sharing your knowledge. RIP
@matthewrussell7802
@matthewrussell7802 6 років тому
Someone give this man a medal. Pure brilliance. Thanks for sharing.
@sreeganeshvr7561
@sreeganeshvr7561 3 роки тому
12:42 Thanks, Brett, whoever you are. Panicked for a few minutes until you chimed in 😂🙌🏾
@bitbyte8177
@bitbyte8177 3 роки тому
lol same.
@hussamcheema
@hussamcheema 5 років тому
Brilliant Lecture ... Thank You :)
@vijayakumark5190
@vijayakumark5190 5 років тому
I pay my sincere thanks to the professor for an extraordinary lecture. Amazing. Good Teachers are the Gods.
@user-eh9yd9se2d
@user-eh9yd9se2d 5 років тому
That was amazing. It was like a mixture of math lecture and play. Thanks professor.
@daripadaiseng
@daripadaiseng 9 років тому
Thanks a lot for sharing this. Now I understand the equation. Maybe tomorrow I will forget about this though, lol.
@WarnerBrosWannaB
@WarnerBrosWannaB 9 років тому
lol watch it again!
@MelvinKoopmans
@MelvinKoopmans 5 років тому
Very good lecture, clear explanation and good pace :) One correction: 44:30 (u*v+1)^n is a polynomial kernel, not a linear kernel.
@girrajjangid4681
@girrajjangid4681 4 роки тому
put n=1 generally, this equation is linear and the value of 'n' denotes the dimension
@asdfasdfasdf383
@asdfasdfasdf383 Рік тому
Kernel trick, that has to be one of the most beautiful ideas I've seen (so far) in any branch of mathematics.
@superteam1
@superteam1 5 років тому
I didn't really want to watch this video from how long it was and I just wanted to get a quick rundown on the topic of SVMs, but I saw the comments and decided to watch the whole thing and, my god, am I glad I did. What an incredible lecturer and he made the topic crystal clear. Anyone struggling with SVMs should 100% find 50 minutes to just sit down and watch this and you'll be so glad you did.
@oguzozturk6402
@oguzozturk6402 5 років тому
Shotout to Vapnik and Winston, loves and respects from Turkey :)
@jackdaw205
@jackdaw205 4 роки тому
"This needs to be in a tool bag of every civilized person" Oh wow, at MIT they have a very specific idea of what 'civilized' means
@Islam101_Uganda
@Islam101_Uganda 4 роки тому
😂😂😂😂
@shapedsilver3689
@shapedsilver3689 4 роки тому
For a second I was going to try to defend them but honestly, I think they kinda do
@teenspirit1
@teenspirit1 4 роки тому
Let's imagine that everyone knows how to separate pluses from minuses optimally. The world would be a... I guess it would be the same.
@i486DX66
@i486DX66 3 роки тому
He stated necessary conditions. Not sufficient.
@bubbletea2223
@bubbletea2223 3 роки тому
The best explanation with both intuition and math I ever learnt among all videos about SVM
@jiawenchen4634
@jiawenchen4634 6 років тому
“It's time for more coffee”
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