Data processing these days is exhibiting a split personality. ‘Cloud’ computing grabs the headlines for sheer scale and computing power, while ‘edge’ computing puts the processing at the ‘coal face’ ...

Machine learning, with its ability to analyze large datasets and identify patterns, is particularly well-suited to address the challenges presented by the vast and complex data generated in ...

The idea that quantum computing could transform medical artificial intelligence (AI) has gained momentum in recent years, driven by advances in cloud-accessible quantum platforms and hybrid computing ...

Machine Learning Fundamentals: Principles and Applications Gain a deeper understanding of artificial intelligence with Machine Learning Fundamentals: Principles and Applications. This course explores ...

Are you contemplating a PhD and interested in economic or social science applications of machine learning? You might be a good fit for our pre-doc position. The Center for Applied Artificial ...

A new study published in Lupus Science & Medicine discusses how machine learning (ML) opens new possibilities for studying lupus disease, from building predictive models, identifying new biomarkers, ...

Data is fundamental to hydrological modeling and water resource management; however, it remains a major challenge in many ...

Classical machine learning (ML) is a powerful subset of artificial intelligence. Machine learning has advanced from simple pattern recognition in the 1960s to today's advanced use of massive datasets ...

Artificial intelligence (AI) is transforming our world, but within this broad domain, two distinct technologies often confuse people: machine learning (ML) and generative AI. While both are ...

Machine learning (ML) models have been increasingly used in clinical oncology for cancer diagnosis, outcome predictions, and informing oncological therapy planning. The early identification and prompt ...