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2. Template (word processing) - Wikipedia

   en.wikipedia.org/wiki/Template_(word_processing)

   The term template, when used in the context of word processing software, refers to a sample document that has already some details in place; those can (that is added/completed, removed or changed, differently from a fill-in-the-blank of the approach as in a form) either by hand or through an automated iterative process, such as with a software assistant.

3. Template (file format) - Wikipedia

   en.wikipedia.org/wiki/Template_(file_format)

   The word "Template" here means "a pre-formatted file type that can be used to quickly create a specific file". Everything such as font, size, color and background pictures are pre-formatted but users can also edit them. The word "Template" also refer to resource where already prepared samples is presented.

4. Training - Wikipedia

   en.wikipedia.org/wiki/Training

   A more recent development in job training is the On-the-Job Training Plan or OJT Plan. According to the United States Department of the Interior, a proper OJT plan should include: An overview of the subjects to be covered, the number of hours the training is expected to take, an estimated completion date, and a method by which the training will ...

5. Microsoft Word - Wikipedia

   en.wikipedia.org/wiki/Microsoft_Word

   Microsoft Word is a word processing program developed by Microsoft.It was first released on October 25, 1983, [12] under the name Multi-Tool Word for Xenix systems. [13] [14] [15] Subsequent versions were later written for several other platforms including: IBM PCs running DOS (1983), Apple Macintosh running the Classic Mac OS (1985), AT&T UNIX PC (1985), Atari ST (1988), OS/2 (1989 ...

6. Training, validation, and test data sets - Wikipedia

   en.wikipedia.org/wiki/Training,_validation,_and...

   A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]

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