Sentence examples for for processing huge amounts of data from inspiring English sources

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It was ignited by search companies like Google and Yahoo, whose business models required new frameworks and techniques for processing huge amounts of data very rapidly.

These include the launch of the open beta of Cloud Dataflow, Google's new service for processing huge amounts of data, as well as an update to BigQuery, which will make the company's bid data database service available in Google's European data centers and introduces row-level permissions.

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In this article, we bring forward an approach of comparing various deep learning techniques for processing huge amount of data with different number of neurons and hidden layers.

The founders previously built Sysomos, the social media monitoring platform that was acquired by Marketwire in 2010, so they have experience processing huge amounts of data and deriving from that useful insights for brands.

Processing huge amounts of data takes a lot of power.

Both of these customers are processing huge amounts of data to gain insight into user behavior.

However, to determine the number of clusters by subjective observation is not suitable for processing huge amount of PolSAR data.

From the intensive experimental results, we find that the RS processing based on cloud computing performs best from the aspects of programming convenience, data management and computational efficiency simultaneously, especially when processing huge amount of data.

The information processing principles of the human mind have turned out to be of particular interest as the mind is capable of processing huge amounts of sensory data and taking adequate decisions for (re- actions based on these analysed data.

The program involves processing huge amounts of customer data and using sophisticated math techniques developed by I.B.M. researchers to predict how the frequent fliers behave.

Indeed, processing huge amounts of images means being able to process huge quantities of data often of high dimensions, which is problematic for most machine learning techniques.

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