What if people could detect cancer and other diseases with the same speed and ease as a pregnancy test or blood glucose meter? Researchers at the Carl R. Woese Institute for Genomic Biology are a step ...

The importance of machine learning has not gone unnoticed, with 64 percent of the 2015 Spark Survey respondents using Spark for advanced analytics and 44 percent creating recommendation systems.

A machine learning approach leverages nuclear microreactor symmetry to reduce training time when modeling power output ...

The 10 hottest data science and machine learning tools include MLflow 3.0, PyTorch, Snowflake Data Science Agent and ...

David Ussery discusses using Machine Learning methods to predict the pathogenicity of a bacterial infection based on genome ...

In a comprehensive Genomic Press interview, Stanford University researcher Eric Sun reveals how machine learning is ...

Generative AI ventures well beyond traditional machine learning. By using multiple forms of machine learning systems, models, algorithms, and neural networks, generative AI offers a new foray into ...

NIMS and its collaborators have developed a model designed to predict the long-term durability of a range of heat-resistant steel materials by performing machine learning while preserving the ...

Machine learning is fast becoming the go-to predictive paradigm for data scientists and developers alike. Of the many tools available for tapping neural networks, Microsoft’s Azure ML Studio ...

Fabs and mask shops also use classical machine learning in the ‘big data’ analysis of all the operation data available to look for ways to improve yield and prevent downtime.” Now, some are exploring ...