Machine-learning phishing website detection system implemented as a Chrome extension with a Flask API backend.
End-to-end machine learning project to predict customer churn using Python
Physics-informed AI system for predicting aircraft bird strike risk using impact force calculations and machine learning techniques.
Machine Learning project that predicts relationship compatibility, compatibility score, and relationship longevity using personality and lifestyle features.
ML Powered customer churn prediction for U.S. insurance 81% accuracy, 21% revenue uplift potential using Python, scikit-learn, SQL, and Power BI
Predicts telecom customer churn using a Random Forest classifier on the Telco Customer Churn dataset. Includes preprocessing, SMOTE for class imbalance, and evaluation via ROC AUC, confusion matrix, and feature importance.
Remote-sensing analysis of land-use and land-cover change in Ibadan Metropolitan Area using Landsat and Random Forest classification (2013–2023).
Add a description, image, and links to the radom-forest topic page so that developers can more easily learn about it.
To associate your repository with the radom-forest topic, visit your repo's landing page and select "manage topics."