Can You Predict Customer Churn ?

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Predict customer churn using Python and Machine Learning.
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#Python #MachineLearning #AI #CustomerChurn

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Опубликовано:

10 июл 2024

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Комментарии : 41

@bhesht 3 года назад

Excellent exploration!

@trochymiak 4 года назад

As always, something interesting thx! :)

@ComputerSciencecompsci112358 4 года назад

Glad you enjoyed it !

@Machconsults 3 месяца назад

Great work honestly

@vamshikrishna6106 4 года назад

Nice Video ! Thank u ! Sir can you upload video, by taking two different datasets for train and test . Just like Hackathons ! And also a video on Time Series Forecasting

@jayceeharb1305 3 года назад

Hey man great vid!!! You have a more current vid on sentiment analysis.... how can i get the data set you use?

@jpaldama9963 4 года назад

verrrrrrry nice. I skimmed. im gonna watch the whole vid now. Thanks for you work, it is very appreciated.

@ComputerSciencecompsci112358 4 года назад

Thanks for the nice comment!

@sanketgadge9060 3 года назад

Good stuff....

@ComputerSciencecompsci112358 3 года назад

Thanks!

@haneulkim4902 3 года назад

Thanks simple and informative video it was very helpful. I have two questions to ask though: 1. How to define churn? ex: for gaming company if user do not login for more than 1week they say user churned but in companies like airbnb their churn would be few months or years. Is there a way to define meaning of churn? 2. What other models are useful in churn prediction other than logistic regression?

@mhmodsalla587 2 года назад

@MeetMoyele 2 года назад

hello, can you share link to a copy of the raw data please?

@jordancampbell5099 2 года назад

It seems there's so many videos on building the model, but not on how to deploy it. How do you then use this to predict churn?

@romangampert9808 2 года назад

Why do you perform label insteand of one hot encoding as the former will implicityl make your model intepret ordinal relationship between the labeled categories ?

@vamshikrishna6106 4 года назад

How can we improve our accuracy and recall score ??

@kailashraizelmaden4684 4 года назад

Thanks alot for the work, sir can you please provide the link for the uploaded cvs file that you have done in second cell.

@4u2kul 3 года назад

its from kaggle you can google it

@natnaelalemayehu9112 4 года назад

Excellent tutorial. I have one question. Why did you use logistic regression? Could you have used other prediction models?

@kenuffff 3 года назад

logistic regression is good for a binary output like churn yes or no, you could use SVM as well for this type of problem

@chibuzoekejiuba6500 4 года назад

Please I am new in machine learning, as I was practicing your tutorial I got this error; ValueError: Number of labels=1409 does not match number of samples=5634. I'd like you to help me correct it.

@vitorgerberweiss 3 года назад

Wtf man, u did almost all that I wanted to do

@nigelandre8875 4 года назад

Hey can you upload your excel as well as code on Github

@MuhammadAhmad-sf1hp 4 года назад

What if Churn value is not provided in the data set, how we can insert the column in data set using the customer ID

@sudhalalwani7443 4 года назад

same question

@richardobonyo7639 3 года назад

You can preprocess in excel using match and index function. Or create an extra column in your dataframe and use if statement and for loop to check customer ID and pick from you data containing the churn parameters to your previous data set which does not have churn data.

@richardobonyo7639 3 года назад

If the data is sorted in order of customer ID number then df ['Churn']=data, should create a new column with the churn data.

@akhilsai9559 3 года назад

How to prevent zero division error?

@639gaurav 3 года назад

can you please tell me , what's wrong in this ?

@639gaurav 3 года назад

File "", line 2 fig,ax = plt.subplots(1,2 figsize=(28,8)) ^ SyntaxError: invalid syntax

@christinekane6979 3 года назад

You’re missing the comma after the 2

@MHPakistan 2 года назад

Yes no for churn how you mentioned this?

@shyamgurunath5876 3 года назад

Using labelencoder & standardscaler before splitting the data to training & testing dataset May lead to over fitting.Most likely in linear models.

@hariharank5773 2 года назад

What is churn?could anyone explain it clearly

@09aysenur98 2 года назад

If a customer churns, it means that they stop doing business with the company. For example, if a Netflix customer churns, it means that they canceled their subscription.

@hassanfirasat3079 2 года назад

Thanks but TotalCharges does contains 11 empty values which can be replaced with numpy NaN and classes are also imbalance. You can find empty values with df.loc[df.TotalCharges == " " , "TotalCharges"] And can replace them df.loc[df.TotalCharges == " " , "TotalCharges"] = np.nan