This is by far one of the easiest explanations covering such complex models. Excellent approach and flow of analysis.
@vimalcalicut
9 ай бұрын
Very informative and clear explanation of ML concepts. Thank you so much!!
@manjusha7526
Жыл бұрын
Perfect and straight to point explanation Thank you for such a wonderful session 😊
@manjusha7526
Жыл бұрын
Sir is there any video in which feature selection is performed on dataset?
@ayushsachdeva4635
Ай бұрын
people who are having error with exited image they just need to run astype('category') function with data[exited]
@karanpatil6097
Жыл бұрын
Very nice and easy way of teaching. Thankyou so much. Very helpful. Really appreciated.
@hamdansiddiqui3294
2 жыл бұрын
Simple, concise, deeply explained thumbs up to you. Appreciated!!!
@DataThinkers
2 жыл бұрын
Glad you liked it.Keep watching. Thanks.
@tohfasiddikabarbhuiya24
2 жыл бұрын
Very informative, crisp and to the point!
@DataThinkers
2 жыл бұрын
Thanks for your comment. Glad you like this video. Keep watching. Thanks
@diegofernandogonzalezlarro6192
2 жыл бұрын
Thank you so much for this tutorial. It is very complete and extremely well explained.
@DataThinkers
2 жыл бұрын
Thanks for your comment. Glad you liked it. Keep watching
@naseemgharibi
Жыл бұрын
amazing work and explanation, thank you.
@neil007sal
2 жыл бұрын
This is Great, please keep Posting more videos frequently. Also please cover NLP and Deep learning project in coming days
@DataThinkers
2 жыл бұрын
Thanks for your comment. Glad you like this Video. Sure 👍
@ashoksahu-uf5mf
Жыл бұрын
thank you for complete lesson
@DataThinkers
Жыл бұрын
Glad you liked it
@許文綾-r1z
2 жыл бұрын
Awesome video, thankful
@DataThinkers
2 жыл бұрын
Thanks
@michaelscott1899
Жыл бұрын
Loved it🤩
@skykhanncanoeboy
2 жыл бұрын
Thanks for the great video!
@DataThinkers
2 жыл бұрын
Thanks for your comment. Glad you liked this video. Thanks
@tatalee9621
Жыл бұрын
Hi, your video is very informative and full of explanation. However, as I know that the rule of thumb is: never mess up with your test set. Always split into test and train sets BEFORE trying oversampling/undersampling techniques! Because oversampling before splitting the data can allow the exact same observations to be present in both the test and train sets. This can allow model to simply memorize specific data points and cause overfitting and poor generalization to the test data. Data leakage can cause you to create overly optimistic if not completely invalid predictive models. So what you think of that?
@justme-yj6ck
3 ай бұрын
This comment really helped me Koz I was able to consider what you wrote there thank you
@vishalvvnagar
2 жыл бұрын
Thanks for sharing 👍🏻
@DataThinkers
2 жыл бұрын
Thanks for your comment.Glad you like this video.keep watching.thanks
@pratikshinde1662
2 жыл бұрын
Informative..
@DataThinkers
2 жыл бұрын
Thanks for your comment. Glad you like this video. Thanks
@kambamnagamunireddy6247
2 жыл бұрын
Thanks for sharing
@DataThinkers
2 жыл бұрын
Thank for your comment.Glad you like this video.keep watching.thanks
@motishreepatel107
7 ай бұрын
You have explained it really well. Thank you for that. But for me any value i am giving, the prediction is always 1. where i might have gone wrong ?
@DataThinkers
7 ай бұрын
Check my code:github.com/DataThinkers/Machine-Learning-Projects-Code
@viplovechander75
2 жыл бұрын
If u have removed the customer ID then how are you identifying which customer is churning.
@DataThinkers
2 жыл бұрын
First of thanks for your comment. Dear, we have trained our model on available features just for "future predictions."(just for training our model) by removing customer ID, which is not affecting our target variable. Suppose a new customer comes. Because we know who he is. We have to input different features to our model for prediction by removing customer ID. We can check the churn rate for this particular customer. hope I'm clear. Let me know if you still have some queries.
@hoangduongvu
6 ай бұрын
Hello, how about if we have a panel data of clients over time? And may be we want to see the impact of changing salary on the decision to stay or quit the bank? Can we do it, please?
@kkmotghare57
6 ай бұрын
Thanks for the awesome explaination. can you please provide the code notebook for practise?
Thank you for such good explanation… can you tell me if we can visualise the predictions as a dashboard in tableau or power bi
@itsme8487
5 ай бұрын
Sir please share the code for the implementation of cat boost algorithm in this data set......
@avinashrauniyar9997
2 жыл бұрын
Thanks a lot
@DataThinkers
2 жыл бұрын
Thanks for your comment. Glad you like this video. Thanks
@arshad1781
2 жыл бұрын
Thanks 👍
@DataThinkers
2 жыл бұрын
Thanks for your comment.Glad you like this video.keep watching.thanks
@ReelzAndLaughs
Ай бұрын
Bro i executed everything...i got the gui interface also.. but while pressing the predict button there is no output showing
@DataThinkers
Ай бұрын
Check my code here : github.com/DataThinkers/Machine-Learning-Projects-Code/blob/main/Predicting%20Employee%20Churn%20Using%20Machine%20Learning%20(1).ipynb
@muditgupta8813
Жыл бұрын
guys please answer a query, while putting on new data do we have to scale that new set of data too in deployment of streamlit??
@bhoomikagv
9 ай бұрын
Hi, Customer Churn Prediction using KNearest Neighbour Model and using machine learning both are same or not,
@radyoalmikyel6881
Жыл бұрын
Hi just i want to know thet we use also x_train resampled in all ML algortithm??
@nikhil_somani
2 жыл бұрын
Dataset not available on given link with the name mentioned. Can you please check that once?
@DataThinkers
2 жыл бұрын
First of all thanks for your comment. now dateset is available on my GitHub repo.thanks
@artbloom08
2 жыл бұрын
getting attribute error in the last line of prediction error--"list object has on attribute called predict "
@DataThinkers
2 жыл бұрын
Send your code in Email.
@vivekgoyale3501
2 жыл бұрын
can you pls share the problem statement & conclusion
@DataThinkers
2 жыл бұрын
Please elaborate your question. Keep watching. Thanks
@samirkumishra4811
Жыл бұрын
Using NLP make a video on fake news detection... Plzzz... Broo
@DataThinkers
Жыл бұрын
Sure i will upload shortly.
@hrishikeshjakanur9702
3 ай бұрын
Can you provide the GUI code
@DataThinkers
3 ай бұрын
Link : github.com/DataThinkers/Machine-Learning-Projects-Code
@ashwinikumar6461
Жыл бұрын
Dear Priyang, Thank you for your precious teaching . Please do provide us a video on python Tkinter for Gui. Also while working out the same i ma getting a comment as "/usr/local/lib/python3.10/dist-packages/sklearn/base.py:432: User Warning: X has feature names, but Logistic Regression was fitted without feature names warnings. warn( ", . Iam getting the same type of comment in all the models, Because of this iam getting differences all the predictions, Request your earnest support.. Thanks in advance.. God bless.
@DataThinkers
Жыл бұрын
Thanks, use and run my code once, also compare it with your code:github.com/PRIYANG-BHATT/Machine-Learning-Projects-Code, sure i will upload on video on tkinter.
@ashwinikumar6461
Жыл бұрын
@@DataThinkers Thank you so much and appreciating your quick response. When i was working with your codes everything was working quite right and smooth. Thanks with gratitude for your timely support. God bless....
@dr.mahaboobbasha1074
Жыл бұрын
Sir, you have done standard scaler for x_train and x_test but not for y_train and y_test. For dependent variables standard scaler not required sir ?
@DataThinkers
Жыл бұрын
It's already scaled because it contains only two values 0 and 1.
@dr.mahaboobbasha1074
Жыл бұрын
Sir..if dependent variable is numeric in nature in that case do we need to scale the y_train and y_test
@TajeswiniHs
2 ай бұрын
At last wt does tat 1 and 0 indicates in tat output
Brooo... Plzzz... Make a video on fake news detection... Plzz
@DataThinkers
Жыл бұрын
Sure👍
@amishakhetani6712
2 жыл бұрын
Dataset not available on given link. can you please give link in description??
@DataThinkers
2 жыл бұрын
Dataset is available on my Github repo. github.com/PRIYANG-BHATT/Datasets-KZitem-Pandas/tree/main/DS Dateset name is Churn_modelling.csv
@amishakhetani6712
2 жыл бұрын
@@DataThinkers, I opened this link. but no any ipynb, CSV, Excel file is available. when i click on Churn_Modelling.csv looks like code. Please check once. this project helps me in my interview. please help me🙏
@DataThinkers
2 жыл бұрын
Churn_Modelling.csv is a dataset file (in CSV file format) just download it and use it Here is the CSV file (Dataset) : github.com/PRIYANG-BHATT/Datasets-KZitem-Pandas/blob/main/DS/Churn_Modelling.csv Here is the code file : github.com/PRIYANG-BHATT/KZitem_Machine_Learning_Projects_code/blob/main/Project%20-%204%20Bank%20Customers%20Churn%20Prediction.ipynb Best of Luck
@dr.mahaboobbasha1074
Жыл бұрын
Sir.. accuracy_score first time it is 0.808 and second time it is 0.79 why sir?
@DataThinkers
Жыл бұрын
Set random_state to particular value. Check code here: github.com/DataThinkers/Machine-Learning-Projects-Code
@sonalikoli384
Жыл бұрын
very nice video please provide the source code.
@DataThinkers
Жыл бұрын
thanks, Link : github.com/PRIYANG-BHATT/Machine-Learning-Projects-Code
@attaulhaq459
Жыл бұрын
shows the erro rthat string could not convert into float plz any body solve the problem
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