Customer Churn Prediction System using XGBoost Regressor, built on Telecom Industry dataset
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Updated
May 1, 2025 - Jupyter Notebook
Customer Churn Prediction System using XGBoost Regressor, built on Telecom Industry dataset
An Analysis and Machine Learning model to understand employee retention and predict churn as part of the Google Advanced Data Analytics Certificate Capstone Project.
U-M MADS: Milestone Project | ML-powered system that detects and classifies racial bias in news articles using supervised and unsupervised learning techniques, to provide comprehensive bias analysis.
This project compares the effects of Ridge (L2) and Lasso (L1) regression models on clinical data.
Machine learning for predicting negative cardiac outcomes in patients with atrial fibrillation (AF)
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