What is Cross Validation and its types?

[@hanman5195]

i did not find proper online stuff on Data science till you come . Now you came i am amazed at watching and learning data science stuff from you. You are my real Guru ,awesome Sir.

[@jammy2003]

Hrithik Roshan who? You're the real Krish! Thanks so much man, saved my ass as I'm reviewing and revising for finals now. God bless and you've earned yourself a subscriber.

[@sshiv908]

just when I started thinking engineering is so difficult, I found you. thanks for such good explaination

[@samixwasup8561]

this is very close to my university course here in Canada, in fact, you have approached it in a simpler way, which is great

[@rishabhnegi9530]

thanks it really removes my headache of understanding that split stuff of k-fold

[@sachinahankari]

Simple and lucid English with examples makes it easy to understand.. don't worry about comments, be cool as you seems to be and do your job of giving knowledge..

[@yuvachandra330]

Crisp and Clear. thank you Krish.

[@prathameshkoli1355]

Thank you so much Krish Sir, As usual Great Explanation😊

[@cha5848]

I have my deep learning exam in few days ur lectures are really helpful for revision

[@aadishjain6838]

easily the best data science channel out there! thank you

[@ujjwalsingh888]

Sessional tomorrow. Couldn't be explained better. Thank you, sir.

[@bhushandeotale3625]

Best explanation got cleared at first instance

[@ashinkajay]

Thank you so much.. God bless you too !

[@chetanapatil8808]

Best Explaination ever!! Thank you Sir

[@MsRAJDIP]

So Detailed explanation as always

[@jasminejubbal5732]

Great videos Krish thank you so much for sharing

[@aravindvasudev7921]

This video was very helpful. Thank You!

[@varunmajithia2470]

Superb!!!!!!!!!! . Simply Excellent And Very Well Explained.

[@surajkhanna1129]

Binge watching your awesome machine learning playlist!

[@sonnix31]

You are the best. Thank you.

[@hejarshahabi114]

Krish you're amazing, to be honest, I have learnt many things regarding data science from your channel keep going, you are doing awesome.

[@harikrishna-harrypth]

Krish Naik, you're a G!!!! Thanks for taking your valuable time to make these videos for us!

[@bhushanchaudhari378]

Excellent videos sir.. thanks alot

[@prodyutdas1474]

Thank you so much for this nice explanation.

[@kurtissac]

Thank you very much Krish

[@gangaholi8600]

Very nice presentation and very much informative.

[@baharylmaz9366]

This video is amazing thanx

[@ameerhussain5405]

First time watching your tutorial Quality content, clear and crisp Subscribed👍 Keep making more!!

[@huangkevin5183]

Thank you Krish. Have been watching your videos for my uni project. Really helpful contents and clear explanations!

[@ruzanb433]

You are Exceptionally good, the clarity about the concept is on point ! Dam

[@rambaldotra2221]

Amazing Thanks a lot Sir

[@sebastianno8]

Great job, finally I understand what is the purpose of cross validation. I appreciate especially the part when you explained how to communicate cross validation to the stake holders. Thanks again

[@MJXed]

700k subscribers with a board, sir, you are a legend! ❤

[@Moneylisey]

very well explained, thank you very much!

[@sandipansarkar9211]

Thanks Krish .Great Explanation

[@seriouscoder1727]

Krish you r awsome teacher

[@shubhangiwaghmare7947]

very well explained.. thank you

[@claudiusandika5366]

Much respect to you, Sir.. for sharing this detailed knowledge for free. May God Bless you always

[@ayushrajput9988]

Thank you soo much sir for this video clears my concepts

[@blablawtf]

You explained it SO well, thank you so much!

[@rashmimbendakaluru7225]

superb sir, hats off for your simplified explanation with comparison too. very helpful sir, looking forward for videos on other validation methods, thank you once again

[@Ali124hdkflc]

Great video.

[@thatguyadarsh]

God Bless You Too.. Thanks!

[@kadhirn4792]

Thanks a ton. You will reap good.

[@ashwaniagarwal6828]

Crystal clear explanation !!!

[@waywaller2630]

Krish! This video simplifies the concept cross validation brilliantly. Good stuff Homie!

[@annperera6352]

Thank you so much sir.

[@radhakrishna.kalluri7192]

Good job Mr. Krishna

[@saikrishnapadarthi987]

I've been watching your videos on ML. These are simply brilliant. Your explanation is awesome. Could you please provide cards at the right top when you are referring to your other videos. it helps us more. Thanks for your efforts brother...

[@ashishtiwari1912]

Excellent video.

[@mahnabraja1086]

very nice informative videos

[@tanishsharma5440]

Thankyou so much

[@benoitmialet9842]

Thank you.

[@tearistovic]

Thank youuu !!!! ❤

[@MysticAngel3224]

Thank you so much for a clear explanation of this concept

[@anandacharya9919]

You are doing great service to students, hats off to you. Can you please mention the order of DS project. Thank you

[@MK-yl7jl]

Awesome Explanation Man. Thank you

[@hassanabdullahi2203]

How comes i didnt subscribe for krish,,Oh man,You got my respect.Thumps up to you

[@samithmadusanka7573]

Nice explanation. Thank you so much. Good luck

[@aditisrivastava7079]

Amazing explaination..........Thanks

[@sanika6916]

Thankyou

[@TJ-wo1xt]

gr8 video

[@debatradas1597]

Thanks

[@osamaakhtar6525]

subscribed! keep up the good work

[@jayshreedonga2833]

thANKS SIR

[@sahilsahil-qz2oo]

Great job Sir, Thank you very much ♣

[@saivikas569]

detailed explantion about CV

[@mukul98m]

please do make a video on different types of encoding teachniqe

[@Funtoosh5395]

Please teach multivariate timeseries data for classification and clustering

[@sumbalkhan9902]

thank you

[@rohitmalhotra2383]

Hi Krish..your videos are awesome..the kind of passion and enthusiasm you have for data science and also for empowering others with same knowledge is exemplary. I am trying to learn data science/ML to employ them in Industrial Systems. Pls help me what approach should i follow. Share sources where i can learn to employ them in Industrial systems.

[@MuhammadUmair-or3or]

no github link?

[@rutdvajrawal7933]

Thanks a lot krish. Do you have a community or a telegram channel

[@kousiksekar1894]

Awesome

[@RinkiSingh-ph6oo]

excellent explanation could u explain genialized linear modal pls👍

[@madhurabhalke2344]

So like for every dataset.. Cross validation is mustt???

[@SararithMaoplus]

Hello, do you have code implementation for Time series cross validation? Thank you so much.

[@060584saurav]

Good Explanation however I have one doubt. The model is trained k times with different datasets so, the hyperparameters of the each model will be different. How to determine and see the best model and its associated hyperparameter. Thank You

[@trend_dindia6714]

When we apply hyper parameters tuning do it apply on k fold or stratified cv

[@shafa-atali7816]

thanks a lot for ur video. Can u kindly tell how to find accuracy of a CNN model using k fold cross validation.

[@nitishreddy4888]

Ok

[@ig2947]

Brilliant..!

[@anirudhashukla1305]

Can some share the link of the project where he has used timeseries cross validation

[@ghostsleep2852]

Will it be a good idea to suffle the data and then perform k fold CV?

[@chiranjeevibelagur2275]

Hi Krish, nice explanation on CV. But can you show in the codes where i find this accuracy for any kind of CV method. Because I'm a little confused about that part. Or please suggest the video if you have already done that

[@lemonade7134]

Low Bias is actually a good thing, right? Because the meaning of low bias is the difference between the actual value and model-predicted value is low. So that's how a model is supposed to be right? (Correct me if I am wrong)

[@rafibasha1840]

Hi Krish,one data means one datapoint or one row

[@raghuramabl6729]

super sir

[@onkarchothe6897]

can you suggest to me the book for cross-validation and k fold validation? which contains with example with solutions?

[@21471adnan]

Really nice video..How to decide which CV to apply ( K told or stratified ) ?

[@ge_song5]

I am using k-fold cross-validation to train my ml model, where k=4, I understand that 4 models are trained with different subsets of input data. So out of the 4 models, which one is my final artifact? Did I misunderstand CV in general?

[@kotesh634]

you take the average accuracy score of the all 4 folds, that is your final one

[@shyamchaurasiya1069]

Thanks!

[@minhadtuashimahmed3873]

Have a little confusion is the test and validation set are the same or different

[@ahsanraza4676]

why we use random_state=40 in k fold coss validation?

[@yogeshwarshendye4857]

I am including some a fraction of my training data for validation. Is it a acceptable thing to do?

[@sivakumarprasadchebiyyam9444]

Hi Krishna, nice video. Could you please let me know cross validation is applied on train data or total data?

[@kotesh634]

the cross validation is applied in the Train data (ex: 80 :20, total observations: 1000, train =800, test=200 , if k=4 then it is 200 each fold, so one of the fold is considered as Cross validation , but each time it will change the FOLD-1,FOLD-2,FOLD-3,FOLD-4 . total 4 times it will calculate the accuracy score then average it and give the final score.

[@hemantdas9546]

In leave one out what is the problem if it has low bias. Ideally algo should have low bias low variance.

[@viveksingh881]

computational power...it will take a lot of time to process completely....

[@subramaniannk3364]

Sir, the purpose of cross-validation is to reduce the variance, not bias, correct?

[@yashub9580]

how we should decide the k value in k fold cv??

[@ankushjamthikar239]

Hi Krish, the video is very intuitive and clearly explained! Just wanted to know, do we need to perform cross-validation during hyperparamter tunning? Or should we do it two times, that is (i) duing hyper-paramter tuning and (ii) then after training the model with optimized paramters? In K-fold cross-validation, we have k models. Which one should we deploy? Thanks in Advanced!

[@JKGMo1995]

you can use Nested cross validation and do both at the same time

[@lavanyasagunthala3801]

Its good sir. But why can't we use random sampling without replacement here.

[@fidaullah3775]

Please tell me what is 10 fold cross validation.? I am confused