Hindi-Cross Validation Using Python In Machine Learning|Krish Naik

Cross-validation is a technique for evaluating ML models by training several ML models on subsets of the available input data and evaluating them on the complementary subset of the data. Use cross-validation to detect overfitting, ie, failing to generalize a pattern.
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[@dakshbhatnagar]

Hindi mein alag hi comfort hai samajhne and samjhaane ka 😊

[@niroop_2004]

In one Video u told Andrew Ng is your online guru, But for me u are my online guru sir. If I got interest in ML then its all because of you. Even our college lectures are not skilled enough to teach ML, U came for all of us as God seriously, I am not exaggerating its a reality. Thank you once again sir for these amazing playlist.

[@maukaladka4100]

Amazing sir…..english toh acha tha hindi main ur bhi smjh aata hnnn

[@prashantshekhar8348]

I know it's very late , and when you will read this comment but your playlist doesn't have Unsupervised machine learning completely. It's right time to make those videos, coz you make things understand easier. And for Gate DA aspirants it will be very helpful.❤️❤️❤️

[@niroop_2004]

Exactlyy sir

[@zaafirc369]

I like your videos even before watching them. Thank youuu sir for listening to us and providing this cross validation implementation video!! Hyper-parameter tuning is now so easy to do. I was always scared by the name "Hyper parameter". I'll be practising this with different different regression models. Can't wait for the next video where you are going to explain other cross validation techniques.

[@shorttube5888]

Good morning sir you inspired me for machine learning ....Thanks a lot

[@123vijit]

Thank you soo much. Waiting for hyper parameter video

[@rohitrohit6883]

such a great video sir

[@abhinavrajsaxena789]

How is your each and every facts are so clear what book should we learn

[@keerthanapillai3087]

HI KRISH SIR, I THINK THERE IS A SLIGHT MISTAKE IN THE R2 SCORE CALCULATION. PLEASE RECHECK THE CALCULATION, INSTEAD IT SHOULD BE R2SCORE(Y_TEST,Y_PRED) MEANING (ACTUAL VALUE ,PREDICTED BY THE MODEL).THANKS

[@abhinavgarg4884]

Bhai r2_score ka formula (ytest,ypred) hogaa ya fir r2_score(ypred,ytest)?? Are both same thing or different. Please clarify

[@lalitalone706]

How do I fix the cross-validation score output for every iteration? when I run the code again and again I get different type of scores. and I want to same score every time. Could you do that?

[@arshad1781]

Good

[@poojarai7336]

i am still not getting the concept of random size? can anyone make me understand?

[@rajeevnayantripathi5370]

If you're talking about random_state, it's just used for reproducibility, ensuring that the same data goes to X_train, X_test, y_train, and y_test every time.

[@niroop_2004]

for example once data is split as train and test, its not that every time we get the same train and test data in the table when we don't mention random size. but if we mention random size = 42 or any number, then any person using that dataset will able to split the same data as you do and even for you also it wont change, next time when u use the random size = 42 then it will same as pervious one.

[@kgtw5506]

i am able to understand better in hindi

[@sanatmishra521]

Please start a podcast

[@yashjaiswal4453]

I am a college dropout....can I learn Data science, get a certificate and get a job?

[@poojakumarirollno9880]

yes you can if you intrested or strong feeling to learn

[@bhaktigupta3043]

Aapko qspr aata hai mare ko samjhna hai

[@dexter4638]

ｐｒｏｍｏｓｍ