Haoyu Cheng, Ph.D., assistant professor of biomedical informatics and data science at Yale School of Medicine, has developed ...

Extracting and analyzing relevant medical information from large-scale databases such as biobanks poses considerable challenges. To exploit such "big data," attempts have focused on large sampling ...

UC Santa Cruz will join three other institutions to establish a transdisciplinary research institute bringing together mathematicians, statisticians, and theoretical computer scientists to develop the ...

Building fast and highly performant data science applications requires an intimate knowledge of how data can be organized in a computer and how to efficiently perform operations such as sorting, ...

Forbes contributors publish independent expert analyses and insights. Writes about the future of finance and technology, follow for more. We live in a world where machines can understand speech, ...

Automating this core facet of data science is essential so that “instead of training being in the hands of a few data scientists, RPA has taken it to the next level by democratizing it by pushing it ...

Strict ethical and professional standards should be applied to the development of algorithms with social impacts to recover public trust in the technology, according to a report by BCS, the Chartered ...

Understand the principles of efficient algorithms for dealing with large scale data sets and be able to select appropriate algorithms for specific problems. Understand and be able to apply the main ...

In the world of data science, there are three core problems: acquiring data, doing the math and taking action. Two of those drive data scientists crazy; the other one they find easy. “Doing the math” ...