GitHub - codewithsanaa/Bankchurnpredict: The Bank Churn Classification project predicts customer churn in the banking sector using machine learning algorithms and EDA. It features a user-friendly interface built with HTML and CSS, with model deployment via Flask. This helps banks identify churn patterns and implement strategies to retain customers.

Name		Name	Last commit message	Last commit date
.ipynb_checkpoints		.ipynb_checkpoints
templates		templates
Bank_Churn_Prediction.ipynb		Bank_Churn_Prediction.ipynb
Copy_of_TelegramBOT_weather.ipynb		Copy_of_TelegramBOT_weather.ipynb
Copy_of_train_yolov8_object_detection_on_custom_dataset.ipynb		Copy_of_train_yolov8_object_detection_on_custom_dataset.ipynb
Customer_Churn_Prediction.pkl		Customer_Churn_Prediction.pkl
app.py		app.py
churn.csv		churn.csv
requirements.txt		requirements.txt

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The Bank Churn Classification project predicts customer churn in the banking sector using machine learning algorithms and EDA. It features a user-friendly interface built with HTML and CSS, with model deployment via Flask. This helps banks identify churn patterns and implement strategies to retain customers.

css customer-retention data-science flask html machine-learning matplotlib numpy pandas python random-forest scikit-learn

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