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e. Sample article layout (click on image for larger view) This guide presents the typical layout of Wikipedia articles, including the sections an article usually has, ordering of sections, and formatting styles for various elements of an article. For advice on the use of wiki markup, see Help:Editing; for guidance on writing style, see Manual ...
This is a Wiki pedia user page. This is not an encyclopedia article or the talk page for an encyclopedia article. If you find this page on any site other than Wiki pedia , you are viewing a mirror site .
Full details can be found in Help:Template, Wikipedia:Templates and m:Help:Advanced templates . A template is a Wikipedia page created to be included in other pages. It usually contains repetitive material that may need to show up on multiple articles or pages, often with customizable input. Templates sometimes use MediaWiki parser functions ...
Text formatting in citations should follow, consistently within an article, an established citation style or system. Options include either of Wikipedia's own template-based Citation Style 1 and Citation Style 2, and any other well-recognized citation system. Parameters in the citation templates should be accurate.
Click edit on any accessible page; Surround the page title you want to create in doubled brackets, e.g., [[Proposed Title]]; Click the Show previewbutton (notthe Publish changes button); Click on the red link revealed. Method 3: saving a red link. Often you will want to have easy continuing access to a page you create.
Article Layout Template. This is a dummy article to help you get started with creating pages in the wiki. The first paragraph is usually a short dictionary-style definition of the subject matter. The gives the reader a quick answer, which may be all they required, and reassures them that they have come to the right page.
Menus & subpages. Art, Decor, etc. User page Hall of Fame. A user's home (page) is their castle. Categories: Wikipedia how-to. Wikipedia help projects. Wikipedia user space.
e. Word2vec is a technique in natural language processing (NLP) for obtaining vector representations of words. These vectors capture information about the meaning of the word based on the surrounding words. The word2vec algorithm estimates these representations by modeling text in a large corpus. Once trained, such a model can detect synonymous ...