Feng, Flora, Charis Li, and Shunyuan Zhang. "Visual Uniqueness in Peer-to-Peer Marketplaces: Machine Learning Model Development, Validation, and Application." Journal of Consumer Research (forthcoming ...

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

Some artificial intelligence models can already resemble the human brain even before having learned anything. This surprising ...

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 ...

Applying Machine Learning (ML) to physiological data poses several challenges. While ML can be effectively used to model well-defined systems, applying it to a system as complex as the human body ...

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 ...

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, ...

Dr. Chris Hillman, Global AI Lead at Teradata, joins eSpeaks to explore why open data ecosystems are becoming essential for enterprise AI success. In this episode, he breaks down how openness — in ...

There's no more important topic than machine learning in the developer space right now as advanced AI constructs like ChatGPT and Microsoft's "Copilot" assistants are transforming the industry. With ...