Sentence examples for models that leverage from inspiring English sources

American Express uses Big Data analytics to detect and prevent fraud in milliseconds and with greater precision, using machine-learning models that leverage billions of historical transactions across millions of card members, resulting in instant fraud alerts for customer protection.

The teams will present models that leverage existing resources with both modest and significant incremental funding.

Business models that leverage a network effect plus stored value, hold the keys to the kingdom.

By enabling new business models that leverage Big Data to deliver killer analytic capabilities and the development of unique killer apps to solve critical business problems.

In future elections, Cohen adds, they plan "to dig in and build more sophisticated models that leverage the particular attributes of the data we collect".

This dearth is particularly concerning given the burgeoning policy implications of the Affordable Care Act and design of medical home models that leverage patient engagement [ 15, 16].

We develop a sequence evolution model that leverages substantially more information in duplicate sequences than used by previous methods and use it to estimate the parameters that govern NAGC in humans: a mean converted tract length of 250 bp and a probability of [Formula: see text] per generation for a nucleotide to be converted (an order of magnitude higher than the point mutation rate).

The plan is to develop a new sales model that leverages their competitive advantages, but some analysts wonder whether bricks-and-mortar operations will prove a drag on the typically high-margin Alibaba.

This paper further presents a model-based service oriented framework that leverages the SCOR models for performance monitoring of construction supply chains.

"The value is really going to emerge from all the tools and innovative business models that can leverage this data to understand risks as they emerge or even before they emerge," he said.

The results of our experiments suggest that even without labeled data, it is possible to build useful machine learning models and that leveraging these models could result in significant gains (at least 8 times better) over a random method.