Sentence examples for sciences machine from inspiring English sources

Spectacular progress in the information processing sciences (machine learning, wearable sensors) promises to revolutionize the study of cognitive development.

In the chemical and biologicals sciences, machine learning-based approaches have been known as (multi-target) Quantitative structure activity relationship (QSAR) methods, which relate a set of predictor variables, describing the physico-chemical properties of a drug target pair, to the response variable, representing the existence or the strength of an interaction.

When math and computer sciences, machine learning and algo-art, hardware and cognitive sciences exponentially accelerate toward each other, it will soon become possible for emotional intelligence to be augmented by "artificial emotional intelligence".

Students have been involved in developing one of the detectors used by B.N.L.'s newest world-class big science machine, the Relativistic Heavy Ion Collider, which has attracted nearly 1,000 researchers from all over the world to work at the lab.

This approach has developed out of the growing availability of data and, in parallel, of methods from data science, machine learning and computational intelligence [48].

Big data, data science, machine learning and now deep learning have been slowly weaving their way into products and companies for the past decade.

The new frontiers for CMOs in the coming years will be data science, machine learning and behavioral insights, which then drives optimization and personalization.

The side effects that ultimately emerged with a handful of their most promising candidates are more attributable to the serendipity of human biology than any systematic shortcomings in the Vertex science machine.

The use of clustering techniques and other ideas from areas such as computer science, machine learning, and uncertainty quantification — along with mathematical and statistical models — are often very useful for data analysis (see, e.g., [1 4] and many other references).

At the time, founder and CEO Jorn Lyseggen talked up the potential to beef up the company's data science, machine learning, and natural language processing capabilities by acquiring startups in the space that have "proven technology".

Companies already have the answer to the problem in the data science, machine learning and artificial intelligence technologies they're likely using in other parts of the business.