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2. 25 Great Resume Templates For All Jobs - AOL

   www.aol.com/news/2014-08-27-great-resume...

   These 25 templates include appropriate examples for positions in finance, admin, graphic design, academia, and more. Some of the designs we selected are traditional and some are more creative, but ...

3. Template:Resume-like - Wikipedia

   en.wikipedia.org/wiki/Template:Resume-like

   Use this template to indicate that an article reads like a résumé or otherwise promotes a biographical subject. Template parameters [Edit template data] This template prefers inline formatting of parameters. Parameter Description Type Status Month and year date Month and year of tagging; e.g., 'January 2013', but not 'jan13' Example January 2013 Auto value {{subst:CURRENTMONTHNAME}} {{subst ...

4. Bootstrap (front-end framework) - Wikipedia

   en.wikipedia.org/wiki/Bootstrap_(front-end...

   Bootstrap (formerly Twitter Bootstrap) is a free and open-source CSS framework directed at responsive, mobile-first front-end web development. It contains HTML , CSS and (optionally) JavaScript -based design templates for typography , forms , buttons , navigation , and other interface components.

5. Résumé - Wikipedia

   en.wikipedia.org/wiki/Résumé

   A résumé or resume (or alternatively resumé), [a] [1] is a document created and used by a person to present their background, skills, and accomplishments. Résumés can be used for a variety of reasons, but most often are used to secure new jobs, whether in the same organization or another.

6. Bootstrapping (statistics) - Wikipedia

   en.wikipedia.org/wiki/Bootstrapping_(statistics)

   This means that samples taken from the bootstrap distribution will have a variance which is, on average, equal to the variance of the total population. Histograms of the bootstrap distribution and the smooth bootstrap distribution appear below. The bootstrap distribution of the sample-median has only a small number of values.

7. Bootstrap aggregating - Wikipedia

   en.wikipedia.org/wiki/Bootstrap_aggregating

   If ′ =, then for large the set is expected to have the fraction (1 - 1/e) (~63.2%) of the unique samples of , the rest being duplicates. [1] This kind of sample is known as a bootstrap sample. Sampling with replacement ensures each bootstrap is independent from its peers, as it does not depend on previous chosen samples when sampling.