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Standard examples of data-driven languages are the text-processing languages sed and AWK, [1] and the document transformation language XSLT, where the data is a sequence of lines in an input stream – these are thus also known as line-oriented languages – and pattern matching is primarily done via regular expressions or line numbers.
The second competition, called the M-2 Competition or M2-Competition, was conducted on a larger scale. A call to participate was published in the International Journal of Forecasting, announcements were made in the International Symposium of Forecasting, and a written invitation was sent to all known experts on the various time series methods ...
The Netflix Prize competition is launched by Netflix. The aim of the competition was to use machine learning to beat Netflix's own recommendation software's accuracy in predicting a user's rating for a film given their ratings for previous films by at least 10%. [39] The prize was won in 2009. 2009 Achievement ImageNet ImageNet is created.
Specific feature - participants have a chance to check the correctness of other contestants' solutions after the coding phase and before final automatic testing (so-called "challenge phase"). UVa Online Judge [19] [17] Contains over 4,500 problems for practising. Hosts regular online competitions. Opened in 1995, it is one of the oldest such ...
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 ...
Two years later, the medium school virtual competition was added to accommodate schools with a student population between 650 and 1300. [13] In 2010, the virtual competition was expanded to include large schools by allowing the second-highest performing school in each state to compete in a large school e-Nationals. [ 14 ]
Naomi Osaka's second-round match at the Australian Open could not possibly have started in a worse way. Osaka strode to the sideline for the changeover, plopped herself down and draped a white ...
A major criticism of data driven instruction is that it focuses too much on test scores, and that not enough attention is given to the results of classroom assessments. Data driven instruction should serve as a “road map through assessment” that helps “teachers plan instruction to meet students’ needs, leading to better achievement”. [19]