It provides a wide variety of machine learning algorithms designed to be scalable and capable of running on large datasets using distributed computing frameworks like Apache Hadoop and Apache Spark.

Department of EECS, University of California at Berkeley, 485 Soda Hall, Berkeley CA 94720-1776, USA Previously at: Institute for Adaptive and Neural Computation, University of Edinburgh, UK.

It can be relatively cheap to gather a lot of bio-signal data. To teach a machine-learning algorithm to find a relationship between bio-signals and health outcomes, however, you need to teach the ...

They also created algorithms that have now become standard tools in the field. Reinforcement learning has also had an unexpected impact on neuroscience. The neurotransmitter dopamine plays a key role ...

In 2017, Ezekiel Emanuel, a well-known oncologist and health policy commentator, said radiologists would soon be out of work thanks to machine learning. That hasn’t happened, but although ...

Get Instant Summarized Text (Gist) A machine-learning algorithm, catGRANULE 2.0 ROBOT, has been developed to predict the potential of proteins to form toxic aggregates linked to neurodegenerative ...

With Season 3 and the return of Verdansk to Warzone looming, Call of Duty's TeamRICOCHET unveils new cheat mitigation tactics alongside continued efforts to shut down cheat distributors.