All Type Of Cross Validation With Python All In 1 Video

[@krishnaik06]

Dont forget to subscribe my vlogging channel to see motivation and Data Science Q&A videos. kzbin.info/door/jWY5hREA6FFYrthD0rZNIw

[@rudrakshkumawat1703]

Hi Krish me and my team working on cloud cost forecasting problem for our organization we have five different vendors azure,aws , snowflake, Databricks,gcp databricks can make videos on this how cloud costs works because we are facing challenges like that we have very less quality data of 6 months each of them CSV file which includes daily based data @krish

[@hassantate1271]

I know it's quite off topic but do anyone know of a good place to watch newly released movies online?

[@rowancade9095]

@Hassan Tate Flixportal

[@hassantate1271]

@Rowan Cade thank you, I went there and it seems like a nice service :D I appreciate it!

[@rowancade9095]

@Hassan Tate no problem :D

[@rog0079]

We need more *All in 1 video* tutorials !! Great work as always !!

[@rhevathivijay71]

Even in college days.. I dint go to class before 10 ..minutes.. But am here waiting even before 15 minutes... Hats off to you krish sir and sudhanshu sir... for DS and ML aspirants..

[@samselvaraj8171]

cringe af

[@sachinpathania1465]

Thanks Krish for this video, i was looking for such content from long time, i had many doubts in K fold and LOOCV, finally all doubts got cleared.

[@aparachitaparachit356]

best trainer... Mr kris sir

[@rambaldotra2221]

Explained everything like Butter. Superb Sir.

[@sonnix31]

Thank you. You are my hero!

[@lorizhuka6938]

Thank you Sir

[@radhakrishna.kalluri7192]

Good work...

[@eramitjangra4660]

train test split also has option of stratify will that be useful for imbalance dataset

[@rohitjagdale4648]

Thanks for the video. Please make video series on pyspark Mllib.

[@satyamtripathi1732]

krish naik sir plss make a video on light gbm and catboost plsss sir apko dil se apna bada bhai maanta hun agar apne nhi banayi video toh main samaj jaoga ki aap mujko chota bhai nhi maante

[@dhairyasansanwal3962]

ok

[@itsme1674]

Thanks 🙏

[@Vinit_Gambhir]

Thanks ❤

[@sunitaskitchen6335]

please make a video on LR classifier trained with ABC algorithm

[@3rd_Son]

thank you

[@MrKevZap]

7:22 Aren't we supposed to use X_train and Y_train instead of X and y in the parameters of cross_val_score function?

[@rajeevnayantripathi5370]

cross_val_score function doesn't require separate training and test sets to be explicitly defined. Instead, it handles the splitting internally based on the cross-validation strategy you provide

[@AI-LearnAndEarn]

When will you make video on Bert ? I recently completed watching your NLP playlist and now I am waiting for the bert session.

[@anshtandon6673]

Sir for the imbalanced Dataset, can't we first handle the imbalance and then do KFold test?

[@shubhamchoudhary5461]

Sir , in machine learning suppose if the model is overfitted & we apply k-fold cross validation on top of that model k-fold(10) , then we get to see lots of variation in cross validation scores right ?. Such as Score = [ 40, 80 , 70 , 80 , 50 , 83.2 , 81,84 ,.......] Means , here diffn between highest & lowest accuracy is ( 84 - 40 = 44) which is very high , means our model is overfitted & not capable to perform on unknown data situation , hence we need to regularise it &do hyperparameter tuning . Make me correct .. Thank you!!!!..

[@pavankumarchahar]

Please upload a Video about different Imbalanced Dataset and how to handle techniques , Various feature engineering approaches etc.

[@vaibhavkhobragade9773]

Thank you @Krish for such a great explanation. I have a question, cross_val_score(model, X, y, cv = k_fold_validation) we are passing X and y from original data without using training data. We also assume that X and y have missing values. If we do imputation on X and y, is there any data leakage problem in cross-validation? if it is how could we handle it?

[@vishalk8905]

It is important to keep in mind that cross-validation is not a way to build a model that can be applied to new data. Cross-validation does not return a model. When calling cross_val_score, multiple models are built internally, but the purpose of cross-validation is only to evaluate how well a given algorithm will generalize when trained on a specific dataset

[@kekkaigenkei]

In that case use pipeline and gridsearchcv

[@gwapdamathtutor2108]

What about nested cross validation method?

[@sachinpatil7088]

Sir please same me ...agar Mai python sekh rahe hua to uska liye front end aane jarure hey Kya like HTML,css, JavaScript and frameworks... help me please

[@aimen1823]

Hello Krish, can you make a session on how to create Ensemble Model(implementation)

[@wahabali828]

you are greate

[@shilpaprusty3319]

Sir please mAke videos on Bayesian optimization

[@himanshu8006]

This is great, thanks by how to use this to predict? I am struggling to apply this on the test data set, can you pls help ?

[@amitroy2976]

What after cross validation? To train our model which fold of data we have to take?

[@hudaali6596]

Please I need classification multi images by crocs validation

[@TJ-wo1xt]

nice one.

[@debatradas1597]

Thanks

[@mmavadat8944]

How to use k fold For image dataset folder

[@add-wisehaalathakikatkeanu5342]

can you show how to use k-fold for 4 class problem with 10 samples each

[@nishikantgurav4500]

krish, in k fold cross validation code you passed directly X and y without splitting so how can the model will know what will be the percentage of training and testing data? cv=10 will take 10 random_states that is each random state is having different data that will give 10 different accuracies. But my question is that how can the model know the percentage of splitting? Is we have to split data with train_test_split giving percentage of splitting and then cross validate with cv=10? please help in this.

[@vishalk8905]

It is important to keep in mind that cross-validation is not a way to build a model that can be applied to new data. Cross-validation does not return a model. When calling cross_val_score, multiple models are built internally, but the purpose of cross-validation is only to evaluate how well a given algorithm will generalize when trained on a specific dataset

[@harikrishnakokkula3207]

hii sir , plz do a video on KD TREE, Ball tree

[@placements_exe1237]

Cross validation 3:00

[@YavuzDurden]

Hi. Why we not just select this 0.98 scored dataset. If we want to choose this 0.98 scored dataset how we can do this? I mean how to achive this dataset scored as 0.98?

[@yunpengliu4072]

Dear sir I'm a big fan of your videos but just a little suggestion, if it's possible could you please change the theme music at the begining which always makes me a little scared.

[@sonalijain3497]

Krish make a detailed vedio on EDA

[@shubhamchoudhary5461]

Mam please check EDA playlist ..

[@vijayananth1053]

B - Benign (Non-cancerous). It's not a type of cancer M - Malignant (Cancerous)

[@gwapdamathtutor2108]

I hear doing cross Val for entire dataset is wrong . Can you explain why not using it in training set

[@atakanbilgili4373]

Yes, my knowledge suggest the same. I think it is due to data leakage. I learnt as you should keep test data until the very end (final prediction).

[@tas9040]

Please start advanced ML DL playlist

[@gayanthadilshan6884]

❤

[@rajeevmayekar1775]

roc_auc_score intuition and implementation video link