As rapidly growing amounts of data are created and used in industry and research environments, there is an increasing demand for people who are able to pursue data-driven thinking and decision-making ...

Devoted to faculty and students that are interested in developing new machine learning algorithms and techniques, and seek to deepen our understanding of existing ones. Machine learning provides the ...

Recent years have seen a significant increase in the availability of large datasets for agriculture applications. Remote ...

TMTPOST -- Google on Friday launched BigQuery AI, a comprehensive platform that enables data scientists and analysts to build ...

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 ...

Collisions between marine vessels and stationary structures, like offshore oil platforms and depleted wellheads, are becoming ...

Embodied learning for object-centric robotic manipulation is a rapidly developing and challenging area in embodied AI. It is ...

The area of machine learning, which is quickly expanding, uses statistical methods and data analysis to teach computers how to learn and make predictions or judgements without being explicitly ...

In this special guest feature, Gary M. Shiffman, PhD, Co-founder and CEO, Consilient, takes a look at Federated Machine Learning, the branch of machine learning that’s sure to be a revolution for FCC ...