Aims To develop prediction models for identifying cases with poor visual outcomes after surgery for primary rhegmatogenous ...

A privacy-preserving marketing framework applies homomorphic encryption to perform machine learning on encrypted ...

Abstract: Precise forecasting of solar power output is crucial for integrating renewable energy into power networks, improving efficiency and dependability. This study assesses the efficacy of several ...

Machine learning is increasingly used in content-based recommender algorithms to guide journal submissions for academic articles. Objective: We sought to evaluate the performance of open-source ...

This project is targeting people who want to learn internals of ml algorithms or implement them from scratch. The code is much easier to follow than the optimized libraries and easier to play with.

An Explainable AI-based Diabetes Risk Prediction System using XGBoost, SHAP, Streamlit, and Power BI for intelligent patient risk analysis and interpretable machine learning predictions. - KrishnaR ...