Objective: This study evaluated the feasibility of using a smartphone app to predict mental health risks in non-clinical adolescents by integrating active and passive data streams within a machine ...

Data mining has become indispensable for dividing heterogeneous customer bases into coherent groups and for nurturing long-term relationships through targeted engagement. Unsupervised learning methods ...

You're probably a little tired of reading or hearing about AI, right? Well, if that's the case, then you're in the right place because here, we're going to talk about machine learning (ML). Yes, it's ...

Accurate crop yield prediction is vital for ensuring global food security, particularly amid growing environmental challenges such as climate change. Although deep learning (DL) methods have shown ...

It’s everywhere, as the author learned the hard way while making as little contact as possible with machine learning and generative artificial intelligence. It’s everywhere, as the author learned the ...

Abstract: Customer segmentation is a method that uses un- supervised machine learning to segment customers by common characteristics, behaviors, and wants. This technique enables companies to market ...

Automated Machine Learning (AutoML) aims to streamline the end-to-end process of ML models, yet current approaches remain constrained by rigid rule-based frameworks and structured input requirements ...

Forbes contributors publish independent expert analyses and insights. Randy Bean is a noted Senior Advisor, Author, Speaker, Founder, & CEO. How does a venerable American brand known for creating the ...