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Deep Learning Simplified Repository (Proposing new issue)
🔴 Project Title : Customer Retention Risk Prediction
🔴 Aim : Predict customer churn risk in the banking sector to help retain high-risk customers by identifying patterns through factors like credit score, balance, and activity levels.
🔴 Dataset : Real-world banking dataset containing features such as customer age, credit score, balance, and tenure.
🔴 Approach : Use at least 3-4 algorithms including an Artificial Neural Network (ANN) for model implementation. Compare the models based on accuracy scores, and perform exploratory data analysis (EDA) to understand key trends and data distributions before building the models.
Approach for this Project: pproach: Preprocess the data, perform EDA, build and compare models ANN, and analyze feature importance. Integrate with Streamlit for predictions, and optionally provide Streamlit deployment links for easy access.
What is your participant role? - gssoc-ext and hacktoberfest
Thankyou
The text was updated successfully, but these errors were encountered:
Deep Learning Simplified Repository (Proposing new issue)
🔴 Project Title : Customer Retention Risk Prediction
🔴 Aim : Predict customer churn risk in the banking sector to help retain high-risk customers by identifying patterns through factors like credit score, balance, and activity levels.
🔴 Dataset : Real-world banking dataset containing features such as customer age, credit score, balance, and tenure.
🔴 Approach : Use at least 3-4 algorithms including an Artificial Neural Network (ANN) for model implementation. Compare the models based on accuracy scores, and perform exploratory data analysis (EDA) to understand key trends and data distributions before building the models.
✅ To be Mentioned while taking the issue :
Thankyou
The text was updated successfully, but these errors were encountered: