Support Vector Machine (SVM) Basic Intuition- Part 1| Machine Learning

In machine learning, support-vector machines are supervised learning models with associated learning algorithms that analyze data used for classification and regression analysis.
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[@esubah1]

wow, wow...I'm only five minutes into this video and I am in awe of how you explain this stuff; you are a great teacher; thanks so much and I will definitely start watching more of your other videos; be safe my friend.

[@TheR4Z0R996]

You're such a Great teacher, thanks a lot and please upload soon the remaining part i can't wait. God bless you

[@suryav3959]

I have been waiting for this video. I didnt understand it from other videos,your explanation is really clear,crisp and easy to understand.

[@birsencal]

By far the best explanation I have come across till date for SVM. Would be brilliant if I could learn in a class from you sir.

[@annan9348]

The best explanation I've come so far! Thank you!

[@kalyanpursunil85]

This is the best explanation I've come across to date on SVM. Thank you for putting together this video and explaining the concepts clearly and concisely. Appreciate it!

[@khushboovyas5932]

Thank you so much sir.. i was waiting for your lecture on SVM for so long.. waiting for the next parts too.. 🙏

[@owaisahmad780]

Thanks krish... I request you to make this video and within two days you accepted my request... Once again thank a lot for making this video...

[@ganeshgunjal4220]

Pursuing course for AI ML.. dont understaand this concept there. then started this video here and idea gets cleared. thanks krish sir. u r really amazing.

[@obuvenkateshyadav8621]

I'm really saying sir. Your session is simply super & your language also interacted

[@kalaivanisivarajan5579]

I never seen such kind of clear explanation. I have seen all your videos. Very good. Please keep going. We need your support. Thank you.

[@adityagurav5065]

Hello sir, I'm an DOT NET Dev and on the path to persue my dream i.e machine learning. I'm amazed by this explanation. Thanks a lot. Will regularly watch your videos now. These videos are super crisp.

[@user-wn6jl1qx6w]

Krish naik sir, you are an excellent teacher. You are transforming the teaching industry and how a topic should be taught and its relevance in industry.

[@svenko333]

This is phenomenal, you are really helping so much people with this type of videos, especially me haha. Keep up the great work man, really

[@bivasbisht1244]

you are the best person for ML and DS in youtube

[@anandib5401]

I brought a bunch of books on ML and SVM, but they all had difficult words and equations in them, Krish made it so simple that I wish I had found this tutorial earlier.

[@anuupadhyaya8833]

This is the best explanation I found regarding SVMs and Kernels.

[@karanghorai5517]

I just had to pause the video and thank you for your wonderful teaching.. really cant thank you enough

[@16876]

Thank you sir, much appreciated!

[@saravananraja6369]

Hi, In the SVM model there is something called soft margin and you missed to talk about that concept in this tutorial. Hope you will do in future. Your videos are awesome. Keep up the good work Krish.

[@karamveersingh8164]

This is one of the best explanations I have seen !

[@midhunskani]

thanks very much waiting for the next part. Explanation is crisp and clear

[@irfanmoosani7771]

Good explanation for a newbie like me. Thanks for summarising all the points covered at the end

[@RishikavsAnnie]

One of the best channels for data science!

[@harishankerkethavath8872]

Thanks a lot sir, I am waiting for part 2 so please do as soon as possible

[@shadmanahmed3666]

Your teaching makes my understanding more clear.Thank you sir.

[@surendrareddy7190]

Thank you sir! Eagerly waiting for next video .

[@palashmoon3808]

Amazing vedio..waiting for the next one

[@kamalikaganguly1245]

Salute to you sir!! now I just want to be a guide like you sir.. how can u ease our studies so well!!😍😍😍😄😄

[@rashmimahendrakar355]

Awesome way of teaching sir..looking forward for more sessions .

[@supongmenwalling6929]

short and to the point...Loved it

[@abhijitmondalabhi2146]

Best clarification. Please, do more videos. Waiting to learn..

[@pratyushranjan887]

You are a legend, bro!

[@ashwiniaparnaelango4753]

That's awsm clearly explained ✌️

[@ezraephrem6791]

The BEst explanation of SVM, appreciate your help

[@vijayabaskaranvenkatraman2389]

super sir i never expected like the way of SVM concept.

[@cynthiamoricordova5099]

I really appreciate all the effort in the different machine learning topics that you make in your videos. Good explanation.

[@143balug]

Thank you krish, waiting for next part.

[@toyinokebule4882]

Wow, this is very impacting, you are good teacher. keep it up

[@Ramesh-rp6jq]

You have unique style in teaching

[@chalmerilexus2072]

After watching MIT video on this topic, I can say that you deserve to be in MIT

[@zindaginamilegidobara3372]

what are talking... Mr. krish is giving explaination like layman .... he is not at all taking about the optimization of hyperplane

[@arunbali7480]

Daaga khol diya sir aapne ❤️

[@computingpower197]

sir you made me to thik ml may be i can do that i am a fullstack developer and i was really frustrated with the math behind ml but you made it learn bad instaractors and teachers from this guy my hommiiiiiiie thankyou sir

[@varunmajithia2470]

Excellent. Superb Explaination

[@sumitgangwar5137]

waooo........ great explanation

[@belfloretkoriciza5279]

Your videos are always easy to understand

[@kuthaardana]

Excellent, sir. Thank you.

[@jones4540]

Thank you very much for clear explanation !!!

[@suwanthiniravinthirakumar8163]

Thank you. SO simple and understandable

[@sriramvenkata8380]

Thank you! Very well explained!

[@purnimanishad3273]

best explanation on KZbin Channel , Speech Less Sir.....................Thanks Sir

[@AyushGupta-kp9xf]

Best explanation !! thanks a lot

[@ManishKumar-qs1fm]

Thank for dis,I love it

[@vasubhagiradhi218]

Excellent....👏👏

[@aparnashrivastava5837]

Thankyou so much for clear & concise explanation

[@shafiqshams3065]

Very nicely explained!

[@MuhammedTausif]

Very good explanation. Understand.

[@harikrishnab4930]

Very good explanation. Thank you.

[@ashishtiwari1912]

The explanation is very clear. Thanx for the video. Subscribing your channel

[@aruiwale]

fantastic explanation!

[@Kishor-ai]

Thanks for this video krish naik sir😍

[@vaibhavpatidar5335]

Thank you krish sir for this❤

[@lakshmireddy8551]

Thanks for the video....it really helps a lot.. :)

[@akshunair3367]

Thank you so much, amazing tutorial

[@bigmugable]

JUST AWESOME!

[@umairshahzad1383]

Great Video!

[@tarajano1980]

You are really good Krish

[@omprakashacharya3810]

onw thing i wonder of krishna sir is , where is the source of energy that comes to him while teaching? He is next level teacher

[@grabngoinfo]

Thank you for sharing!

[@yibeyibe389]

Great video!

[@alele5410]

hey! am alexander..i have seen most of your totorials. it is good and very nice explanation..plz post the tutorials related to ANN and different remote sensing data application by this machine learning algorithm

[@subhanullahasim721]

wonderful, got a like and subscription

[@abdulrawoof1570]

Vera level 👌

[@sandipansarkar9211]

superb explanation. Thanks

[@aadityaagrawal11]

Great Explanation

[@Bws098]

You are not the best, You are best of all the bests. ;)

[@abhinaykrishna9909]

Fun Fact: You have used "Particular" word for 96 times. Getting close to a Century!! :) :) Good work by the way. Very helpful

[@krishnaik06]

Thanks for counting :)..but I think u should focus on the class :)

[@Laxmikumari-bd4sy]

Love your videos

[@deltechdiaries5907]

excellent explanation!

[@abidson690]

Amazing explanation

[@yukeshnepal4885]

thank you sir very very much sir!!

[@sk-gj8iz]

Hi .. I think kernel SVM tries to transforms points from SOME dimensions to the OTHER dimensions where the points r linearly separable or almost separable but not necessarily from lower to higher dimensions.we try different functions .... sometimes in real world we can’t Visualize the data ...so we believe in SOME dimensions data might be separable....or might not be .. if it gives good results according to the metrics we have chosen, it’s nice else we go for other algorithms ...thanks for making this algorithm simple.nice explanation brother ...👌👌👌

[@ashish-blessings]

God send. Thank you so much sir. Charan sparsh.

[@swatibogawat8368]

Very Clearly explained

[@xXmayank.kumarXx]

you have explained the solution but not the problem and why this approach is used.

[@shyamsundarb2547]

This Helped me a lot and nice intro music

[@amitjajoo9510]

thanks sir for making such video

[@vcjayan8206]

Good explanation,,thanks

[@gurudevsutar1810]

Thank you Krish Sir

[@tanjibahmed1968]

thanks for your explaination on this topic

[@deekshakulshreshtha]

Nice explanation, I especially come for the mathematical part..

[@kunalgulati3358]

Great video

[@TinyTalksInsights]

Sir have Good teaching skill

[@prasadinipadwal3641]

superb explantion

[@nishaverma5263]

Thank you kris😊😊

[@rusiraliyanage6643]

very convinient sir :)

[@neha_Sharma-vd7hz]

amazing video

[@sravanyesh6125]

Thankyou sir helped alot❤

[@shobithas8269]

Thanks for a clear explanation. Would be interested to hear SVR (support vector regression)algorithm from you. How to perform hyper parameter tuning in SVR algorithm.

[@oianmol]

amazing!