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.

[@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.

[@TheR4Z0R996]

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

[@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!

[@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.

[@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...

[@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.

[@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.

[@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.

[@obuvenkateshyadav8621]

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

[@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

[@khushboovyas5932]

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

[@16876]

Thank you sir, much appreciated!

[@bivasbisht1244]

you are the best person for ML and DS in youtube

[@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 !

[@shadmanahmed3666]

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

[@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.

[@irfanmoosani7771]

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

[@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

[@kamalikaganguly1245]

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

[@midhunskani]

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

[@ezraephrem6791]

The BEst explanation of SVM, appreciate your help

[@RishikavsAnnie]

One of the best channels for data science!

[@cynthiamoricordova5099]

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

[@rashmimahendrakar355]

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

[@supongmenwalling6929]

short and to the point...Loved it

[@jones4540]

Thank you very much for clear explanation !!!

[@surendrareddy7190]

Thank you sir!
Eagerly waiting for next video .

[@harishankerkethavath8872]

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

[@Ramesh-rp6jq]

You have unique style in teaching

[@vijayabaskaranvenkatraman2389]

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

[@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

[@suwanthiniravinthirakumar8163]

Thank you. SO simple and understandable

[@ashwiniaparnaelango4753]

That's awsm clearly explained ✌️

[@abhijitmondalabhi2146]

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

[@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

[@harikrishnab4930]

Very good explanation. Thank you.

[@toyinokebule4882]

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

[@aparnashrivastava5837]

Thankyou so much for clear & concise explanation

[@143balug]

Thank you krish, waiting for next part.

[@arunbali7480]

Daaga khol diya sir aapne ❤️

[@purnimanishad3273]

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

[@pratyushranjan887]

You are a legend, bro!

[@kuthaardana]

Excellent, sir. Thank you.

[@palashmoon3808]

Amazing vedio..waiting for the next one

[@MuhammedTausif]

Very good explanation. Understand.

[@belfloretkoriciza5279]

Your videos are always easy to understand

[@sriramvenkata8380]

Thank you! Very well explained!

[@akshunair3367]

Thank you so much, amazing tutorial

[@sumitgangwar5137]

waooo........ great explanation

[@grabngoinfo]

Thank you for sharing!

[@varunmajithia2470]

Excellent. Superb Explaination

[@ManishKumar-qs1fm]

Thank for dis,I love it

[@vaibhavpatidar5335]

Thank you krish sir for this❤

[@aruiwale]

fantastic explanation!

[@vasubhagiradhi218]

Excellent....👏👏

[@gurudevsutar1810]

Thank you Krish Sir

[@Laxmikumari-bd4sy]

Love your videos

[@aadityaagrawal11]

Great Explanation

[@tarajano1980]

You are really good Krish

[@lakshmireddy8551]

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

[@TinyTalksInsights]

Sir have Good teaching skill

[@AyushGupta-kp9xf]

Best explanation !! thanks a lot

[@abidson690]

Amazing explanation

[@Kishor-ai]

Thanks for this video krish naik sir😍

[@ashishtiwari1912]

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

[@sandipansarkar9211]

superb explanation. Thanks

[@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 :)

[@subhanullahasim721]

wonderful, got a like and subscription

[@umairshahzad1383]

Great Video!

[@yibeyibe389]

Great video!

[@ashish-blessings]

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

[@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

[@tanjibahmed1968]

thanks for your explaination on this topic

[@shyamsundarb2547]

This Helped me a lot and nice intro music

[@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

[@sravanyesh6125]

Thankyou sir helped alot❤

[@deltechdiaries5907]

excellent explanation!

[@shafiqshams3065]

Very nicely explained!

[@yukeshnepal4885]

thank you sir very very much sir!!

[@hamidnawaz1422]

wonderful explanation...from Pakistan

[@xXmayank.kumarXx]

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

[@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 ...👌👌👌

[@vcjayan8206]

Good explanation,,thanks

[@kunalgulati3358]

Great video

[@davidhovakimyan3146]

Thank you very much!!!

[@neha_Sharma-vd7hz]

amazing video

[@alphaman3765]

You helped me to learn by brain and not by-heart

[@prasadinipadwal3641]

superb explantion

[@betanapallisandeepra]

thank you for doing this..

[@bigmugable]

JUST AWESOME!

[@GANESHPATIDAR-qc7us]

Excellent

[@abdulrawoof1570]

Vera level 👌

[@swatibogawat8368]

Very Clearly explained

[@Bws098]

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

[@aisyanadyadamarcha8317]

Hey, kris!! it's nice watching your video cuz it's so understandable for me. May I ask about a topic related to CNN + SVM? How can we combine those classifiers to images in python? Thanks a lot if you wanna reply this :)