首页|New Study Findings from Siberian Federal University Illuminate Research in Machi ne Learning (Revolutionizing physics: a comprehensive survey of machine learning applications)
New Study Findings from Siberian Federal University Illuminate Research in Machi ne Learning (Revolutionizing physics: a comprehensive survey of machine learning applications)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on artificial intell igence are discussed in a new report. According to news reporting from Krasnoyar sk, Russia, by NewsRx journalists, research stated, "In the context of the 21st century and the fourth industrial revolution, the substantial proliferation of d ata has established it as a valuable resource, fostering enhanced computational capabilities across scientific disciplines, including physics." Our news journalists obtained a quote from the research from Siberian Federal Un iversity: "The integration of Machine Learning stands as a prominent solution to unravel the intricacies inherent to scientific data. While diverse machine lear ning algorithms find utility in various branches of physics, there exists a need for a systematic framework for the application of Machine Learning to the field . This review offers a comprehensive exploration of the fundamental principles a nd algorithms of Machine Learning, with a focus on their implementation within d istinct domains of physics. The review delves into the contemporary trends of Ma chine Learning application in condensed matter physics, biophysics, astrophysics , material science, and addresses emerging challenges. The potential for Machine Learning to revolutionize the comprehension of intricate physical phenomena is underscored."
Siberian Federal UniversityKrasnoyarskRussiaEurasiaCyborgsEmerging TechnologiesMachine Learning
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