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The Netflix Prize is one such competition. Since then there have been several platforms developed on the idea of data science competitions. Research has been completed on how competition can improve research performance. Companies like JPMorgan Chase also run internal contests involving large numbers of employees. [2]
While data-driven design does prevent coupling of data and functionality, in some cases, data-driven programming has been argued to lead to bad object-oriented design, especially when dealing with more abstract data. This is because a purely data-driven object or entity is defined by the way it is represented. Any attempt to change the ...
The Latin word data is the plural of datum, "(thing) given," and the neuter past participle of dare, "to give". [6] The first English use of the word "data" is from the 1640s. The word "data" was first used to mean "transmissible and storable computer information" in 1946. The expression "data processing" was first used in 1954. [6]
Data-driven learning (DDL) is an approach to foreign language learning. Whereas most language learning is guided by teachers and textbooks, data-driven learning treats language as data and students as researchers undertaking guided discovery tasks. Underpinning this pedagogical approach is the data - information - knowledge paradigm (see DIKW ...
Download as PDF; Printable version; ... and use of free statistics software. ... for summarizing data, and to make data-driven decisions. ...
NYC BigApps is an annual competition sponsored by the New York City Economic Development Corporation.It provides programmers, developers, designers, and entrepreneurs with access to municipal data sets to build technological products that address civic issues affecting New York City.
Data-driven models encompass a wide range of techniques and methodologies that aim to intelligently process and analyse large datasets. Examples include fuzzy logic, fuzzy and rough sets for handling uncertainty, [3] neural networks for approximating functions, [4] global optimization and evolutionary computing, [5] statistical learning theory, [6] and Bayesian methods. [7]
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