Notebook-1: www.kaggle.com/abhishek/30-days-create-folds Notebook-2: www.kaggle.com/abhishek/competition-day-1-baseline Please subscribe and like the video to help me keep motivated to make awesome videos like this one. :)

I just saw your video thrice, searched for what is kfold once more. And then I was able to understand your code mostly. Since its my first time, I guess I have such a feeling. And the ones after for loop was amazing. I need some more practice to think sequentially that way. Thanks once again for the amazing tutorial.

I love those walkthrough especially in a competition like this , any more coming ?

Hi Abhishek, when I started reading your book AAMLP, I felt a bit confused while creating the folds. But after watching this video, everything has become crystal clear. Thanks a lot for such lucid and crisp explanation.

Thanks for giving us a place to start, I was absolutely clueless on what do before this video

Great Content Mr.Abhishek, Keep up the good work

I am new to DS ML and kaggle as well and I was confused how to start with kaggle and your tutorials cleared a lot more concepts ..Thank you so much..

Damn it 20 days ,and I'm seeing this now! I feel sad for missing out but I'm finally here

Thanks Abhishek sir!😀 I learned a lot, this will improve my level of coding. Will follow your all upcoming videos.Thanks Again for channel!!

Thanks for this video. It was helpful. Please elaborate and explain a little bit more so that if we messed up with concept during these 15 days, those concepts may get cleared.

A thousand thanks!! Your tutorials are the best :) I will purchase your book

Thank you for this tutorial, you videos are really helpful

thank you, this help me a lots!

Great Explanation

This is friggin gold.

You deserve millions of suscribers....

Your video was very useful for me.thank you very mach for your nice explanations.

Thank you for your amazing work. I'm learning alot from you

26:40 i love this xD

Thank you, nice video

Really appreciate your video, learnt a lot from it

It was A little harder and thank you for the great help...

@Abhishek sir, can you please create a video on pipeline especially performing feature engineering (feature interaction to create new features) through pipeline? This will be really helpful. Thank you

You are a legend.

Wow! Great work! Thank you!

wow great work, genuine thanks!

@1:56 you are saying… ….you can just simply use k-Fold, All you need to do is you have to see if the distribution of data is same in each fold if it is not use others… I want ask how you will know by looking at histogram that the distribution of data is same in each fold?

Thank you so much for this! Can you explain why we do df_train.loc[valid_indices...] and not train_indices?

Thanks a lot 😊

Hi at 4:37 you says we don't need train indicies we need valid indicies. Can you explain reason behind it please?

I was running this following cell final_predictions = [] for fold in range(5): xtrain = df[df.kfold != fold].reset_index(drop=True) xvalid = df[df.kfold == fold].reset_index(drop=True) xtest = df_test.copy() ytrain = xtrain.target yvalid = xvalid.target xtrain = xtrain[useful_features] xvalid = xvalid[useful_features] ordinal_encoder = OrdinalEncoder() xtrain[object_cols] = ordinal_encoder.fit_transform(xtrain[object_cols]) xvalid[object_cols] = ordinal_encoder.transform(xvalid[object_cols]) xtest[object_cols] = ordinal_encoder.transform(xtest[object_cols]) model = XGBRegressor(random_state=fold, n_jobs=4) model.fit(xtrain, ytrain) preds_valid = model.predict(xvalid) test_preds = model.predict(xtest) final_predictions.append(test_preds) print(fold, mean_squared_error(yvalid, preds_valid, squared=False)) But getting the following error AttributeError Traceback (most recent call last) in 5 xtest = df_test.copy() 6 ----> 7 ytrain = xtrain.target 8 yvalid = xvalid.target 9 /opt/conda/lib/python3.7/site-packages/pandas/core/generic.py in __getattr__(self, name) 5463 if self._info_axis._can_hold_identifiers_and_holds_name(name): 5464 return self[name] -> 5465 return object.__getattribute__(self, name) 5466 5467 def __setattr__(self, name: str, value) -> None: AttributeError: 'DataFrame' object has no attribute 'target' Can't figure out what happened

Hello sir, can you reopen the data? This contest is no longer available. Thank you.

Hi Abhishek, Thx for the great content. I just want to know name of below technique you used. - in each fold, you fit the model with training data of the fold. - with this model, you make prediction test data, and stack this prediction - finally you average the predictions of test data at the end. this is not cross validation, not out of fold prediction whatever.What is it called?

Thank you!

Sir,I'm watching your video,how can I download the datasets inyour video？I can't fork your project from kaggle

Amazing ! ;)

Hey Abhishek just wanted to ask if challenge is open now. Or it is closed

i have one question, after applying cross-validation, how can I select the best model ( through which I can make predictions )??

Hi Abhishek! thanks again and again for your valuable videos! My question is about the autocompletion will codding in kaggle notebook ! plz is there any way to get the autocompletion in kaggle notebook without using the Tab key.

Thankuu so much sir

Hi Abhishek. Can I get this dataset for practice ? It would be of great help if I get this as csv in my local for learning.

Hi Abhishek, I have started the playlist, Is there a way you can post the original data as its not available coz the competition is closed. I am not able to follow this video hands on due to the data issue.

Keep it up bro

Is there any interesting story behind random_state = 42;

Could some one pls do explain me why he is assigning kfold value on train data set only on valid indices

when i tried oridinal encoding to tranform test data i got error of unknown category but in Abishek sir he didnt got error why this happned BTW i didnt used it inside for loop i tried to do it out side for and was goin to use gridsearch CV

Thanks for the tutorials, they were really helpful. I am not a participant so I was wondering if there is a way for me to get the train and test data. Still gonna sponge off the content and other's notebooks but was wondering if I could do it on my own too.

I loved the video, but I have one question that. How target column is calculated?

Hello guys, I am still currently having a hard time understanding this block of code kf = model_selection.KFold(n_splits=5, shuffle=True, random_state=42) for fold, (train_indicies, valid_indicies) in enumerate(kf.split(X=df_train)): df_train.loc[valid_indicies, "kfold"] = fold particularly this line, df_train.loc[valid_indicies, "kfold"] = fold, why excatly are we doing this? I can't seem to wrap my head around it

Thank you for this video, sir @Abhishek Thakur. Quick question, at 5:45 duration, you are updating the valid_indices with fold (df.loc[valid_indices,'kfold'] = fold), and in the next line when you type head, all instances including the train_indices get updated with the fold value. Can you please explain this? I didn't understand how the train_indices updated with the fold value. Thank you

What is your dark theme setup ? Looks really good.

2:05 Do anyone know in which video the kfolds mentioned earlier? Or let met just ask it here, what is the reasoning behind creating the folds? Thanks!

I am trying to read train_folds data like pd.read_csv("../input/30days-folds/train_folds.csv") but its throwing file not found. Can you tell me how I can refer your public uploaded dataset

Sir, Who Missed registration 30daysofml challenge he/she can participant these competition using his kaggle account If can, How to get competition link?

On which day of "30 days of ML "was the "kfold" stuff explained ?

Dear Prof. thank you very much for your effort,. After the day no. 15 I didn't receive any mail, and from that day the rules of competition is not clear for me.

What is the use of putting index=false?

Sir, why did we create a seperate file with Folds ? Can't we use that for cross_val_score ? Please let me knkow, I'm just trying to understand why create a Folds file and iterate ourselves, while cross_val_score does that for us. Pretty new here so trying to connect the dots. Thanks in Advance.

Hello sirrr , I'm following this playlist since day 1 as I was late for my enrollment I'm not able to make a notebook in competition So what should I do now Like should I jst go through it ? Or make some private notebooks for reference..???

Sir, when i am trying to add df_test= "../30-/test.csv file, it is showing error. Would i have to download test.csv file too and add here? Or i directly use it from competition data? If it is. How will i do it then? @Abhishek Thakur

Can anyone share input dataset plz? I'm late to competition, and access restricted to participants only. Thanks

When running the loop to set the kfold column I get "Your notebook tried to allocate more memory than is available. It has restarted." Do you have more memory allocated to your account ? If yes, how does one increase allocated account memory.

Hlo sir... What's the time when u upload submission?

HELP

Please, do not read the code. Just, explain.......:)