The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...

Overview Kaggle projects provide real-world experience in AI and machine learning.Participants gain practical skills in NLP, computer vision, and predictive mod ...

Classic fault detection and classification has some classic problems. It’s reactive, time-consuming to set up, and any product change involves significant man-hours. Even then, it still misses a lot ...

A multinational collaboration at Eitri medical innovation center in Bergen, Norway, has used machine learning models to identify patient groups at risk of being mistreated.

CNN and random forest model to detect multiple faults in bifacial PV systems, including dust, shading, aging, and cracks. Using simulated I-V curves and a 180-day synthetic dataset, the model achieved ...

Miniaturized electronics and intricate objects require a certain finesse. Researchers have looked into the development of a ...

Understanding molecular diversity is fundamental to biomedical research and diagnostics, but existing analytical tools ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...