All work
Applied MLSide project2024ML Engineer
Customer Churn Prediction Model
Logistic regression on Telco Customer Churn
Pythonscikit learnPandas
One line summary
Feature engineering, class balancing, outlier handling, and a full evaluation suite including confusion matrix, ROC curve, and feature importance.
Status
Detailed case study is in progress. The summary above and the metadata in the header are accurate. Architecture diagrams, hardest technical challenges, and full results writeups are being authored in the coming days.
What this project covers
Feature engineering, class balancing, outlier handling, and a full evaluation suite including confusion matrix, ROC curve, and feature importance.
Role
ML Engineer.
Stack
- Python
- scikit learn
- Pandas