A new study suggests that lenders may get their strongest overall read on credit default risk by combining several machine learning models rather than relying on a single algorithm. The researchers ...

Background Remission and low-disease activity are recommended targets in systemic lupus erythematosus (SLE), yet many ...

Abstract: Predicting volatile commodity prices is challenging due to frequent outliers, which compromise traditional models like Random Forest (RF) that rely on Mean ...

The lack of precise, autonomous tools for monitoring and classifying cattle behavior limits farmers’ ability to make proactive and informed decisions regarding grazing and herd management. Currently, ...

With the accelerating pace of urbanization, the issue of air pollution has become increasingly severe. Notably, carbon monoxide (CO), as a prevalent harmful gas, poses potential threats to both human ...

This project is built to predict passenger survival on the Titanic using supervised machine learning models. It follows a complete ML pipeline from data exploration to model evaluation.

Implement Linear Regression in Python from Scratch ! In this video, we will implement linear regression in python from scratch. We will not use any build in models, but we will understand the code ...

Abstract: Pipeline failure prediction is crucial in ensuring optimal pipeline maintenance strategies. This work applies a Random Forest Regression model (RF) for failure prediction of pipeline using ...

Supervised Machine Learning using SciKit and other tools to do PCA, SVM, random forests, etc. for facial recognition and predictive decision making.