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This is my first app created to predict customer churn. (Using ML Logistic Regression model)

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amindadgar/customer-churn-app

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customer-churn-app

This is my first app created to predict customer churn. (Using ML Logistic Regression model)

We predict the value of customer churn in this application.
Example customer input:
customer = {"contract": "two_year", "tenure": 12, "monthlycharges": 10}
output:
{'churn': False, 'churn_probability': 0.1754496030637589}
We've saved our model and the DictVectorizer in churn-model.bin file.
We've used Procfile for heroku app to be able to run.
Files such as Pipfile, Pipfile.lock and Dockerfile was not needed for the heroku app.

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This is my first app created to predict customer churn. (Using ML Logistic Regression model)

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