Commit History
-
Update README.md
Verified signatured577ec6
-
Update README.md
Verified signature44d42f9
-
Update README.md
Verified signature6bfbc0e -
Update README.md
Verified signature731017e -
Upload 3 files
Verified signaturefb3815f -
Delete Data
Verified signature379d337 -
Create Data
Verified signature188451d -
Update README.md
Verified signature9643318 -
Delete Bank_Customer_Churn_Prediction_using_Artificial_Neural_Networks.ipynb
Verified signature38e20df
-
Update README.md
Verified signature72cd977 -
Update README.md
Verified signature112a70a -
Update README.md
Verified signaturea3ee830
-
Update README.md
Verified signaturea0bda43 -
Upload Bank_Customer_Churn_Prediction_using_Artificial_Neural_Networks.ipynb
Verified signature# 🏦 Bank Customer Churn Prediction — Neural Network Classifier ## 🧩 Overview Customer churn is one of the most critical challenges faced by the banking and financial industry. It directly impacts long-term profitability, customer acquisition costs, and overall business growth. This project leverages **Deep Learning (Artificial Neural Networks)** to predict whether a customer is likely to leave the bank within the next 6 months. By identifying customers at risk of churn early, banks can take **proactive retention actions**, such as improving engagement, adjusting product offers, or providing personalized incentives. --- ## 🎯 Objective As a data scientist working for a retail bank, your goal is to build and evaluate a **Neural Network–based classifier** capable of predicting customer churn. The model helps answer the question: > “Which customers are most likely to leave the bank in the near future?” This insight empowers management teams to: - Target at-risk c…f980c93 -
Update README.md
Verified signature8b27a61 -
Create README.md
Verified signaturecb2d766 -
initial commit
Verified signaturefa6e718