A machine-learning algorithm demonstrated the capability to process data that exceeds a computer's available memory by identifying a massive data set's key features and dividing them into ...

Two new studies from the Department of Computational Biomedicine at Cedars-Sinai are advancing what we know about using ...

Advances in machine learning for materials science, data-driven materials prediction, autonomous synthesis and characterization, and data-guided high-throughput exploration, can now significantly ...

We investigate the data-driven newsvendor problem when one has n observations of p features related to the demand as well as historical demand data. Rather than a two-step process of first estimating ...

EMBL-EBI scientists and collaborators at Heidelberg University have developed CORNETO, a new computational tool that uses ...

As machine learning is becoming more prominent, specific job roles and educational routes are emerging too. The focus of both disciplines, however, does remain distinct.

Upon completion of this course, participants should be able to: ¿ Understand how big data and machine learning can complement traditional data and analytical techniques in macroeconomic analysis and ...