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Sometimes, when you have undesirable whitespace, the best way to solve the problem is to expand the article (with suitable content). Sometimes, a minor fix will help eliminate or reduce whitespace. This may involve adding or removing one blank line from some part of the page, re-ordering templates, or the use of a gallery for multiple images ...
Python sets are very much like mathematical sets, and support operations like set intersection and union. Python also features a frozenset class for immutable sets, see Collection types. Dictionaries (class dict) are mutable mappings tying keys and corresponding values. Python has special syntax to create dictionaries ({key: value})
As a consequence of its syntax, Whitespace source code can be contained within the whitespace of code written in a language that ignores whitespace – making the text a polyglot. [2] Whitespace is an imperative, stack-based language. The programmer can push arbitrary-width integer values onto a stack and access a heap to store data.
A second common application of non-breaking spaces is in plain text file formats such as SGML, HTML, TeX and LaTeX, whose rendering engines are programmed to treat sequences of whitespace characters (space, newline, tab, form feed, etc.) as if they were a single character (but this behavior can be overridden).
In an off-side rule language, indentation white space is syntactically significant. In the satirical and contrarian language called Whitespace, whitespace characters are the only significant characters and normal text is ignored. Good use of white space in source code can group related logic and make the code easier to understand. Excessive use ...
In computational linguistics and computer science, edit distance is a string metric, i.e. a way of quantifying how dissimilar two strings (e.g., words) are to one another, that is measured by counting the minimum number of operations required to transform one string into the other.
Word2vec is a group of related models that are used to produce word embeddings. These models are shallow, two-layer neural networks that are trained to reconstruct linguistic contexts of words. Word2vec takes as its input a large corpus of text and produces a vector space , typically of several hundred dimensions , with each unique word in the ...
At any particular point in the execution, we can group the vertices of the graph into "buckets", according to their rank. We define the buckets' ranges inductively, as follows: Bucket 0 contains vertices of rank 0. Bucket 1 contains vertices of rank 1. Bucket 2 contains vertices of ranks 2 and 3.