Sparse data can impact the effectiveness of machine learning models. As students and experts alike experiment with diverse datasets, sparse data poses a challenge. The Leeds Master’s in Business ...

Embodied artificial intelligence (AI) systems are robotic agents that rely on machine learning algorithms to sense their ...

Microsoft updated its machine learning dev tooling with ML.NET 2.0 and a new version of Model Builder. ML.NET is the company's open source, cross-platform machine learning framework for .NET ...

The data science and machine learning technology space is undergoing rapid changes, fueled primarily by the wave of generative AI and—just in the last year—agentic AI systems and the large language ...

If you rotate an image of a molecular structure, a human can tell the rotated image is still the same molecule, but a machine-learning model might think it is a new data point. In computer science ...

Machine learning is based on the idea that a system can learn to perform a task without being explicitly programmed. Machine learning has a wide range of applications in the finance, healthcare, ...

A research group has developed an innovative machine learning technology that enables predictions beyond the distribution of training data and demonstrated its effectiveness in materials research. The ...

DURHAM, N.C. – A machine learning model developed by Duke Health researchers can differentiate normal cognition from mild cognitive impairment using retinal images from the eye. The model analyzes ...