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  2. Venn diagram - Wikipedia

    en.wikipedia.org/wiki/Venn_diagram

    A Venn diagram is a widely used diagram style that shows the logical relation between sets, popularized by John Venn (1834–1923) in the 1880s. The diagrams are used to teach elementary set theory, and to illustrate simple set relationships in probability, logic, statistics, linguistics and computer science.

  3. File:AI relation to Generative Models subset, venn diagram.png

    en.wikipedia.org/wiki/File:AI_relation_to...

    File:AI relation to Generative Models subset, venn diagram.png. Size of this preview: 600 × 600 pixels. Other resolutions: 240 × 240 pixels | 480 × 480 pixels | 768 × 768 pixels | 1,024 × 1,024 pixels. Original file ‎ (1,024 × 1,024 pixels, file size: 102 KB, MIME type: image/png) This is a file from the Wikimedia Commons.

  4. Reformatted to look more like a Venn diagram and less like a bullseye target: 06:07, 19 February 2023: 499 × 499 (52 KB) The Original Benny C:

  5. Euler diagram - Wikipedia

    en.wikipedia.org/wiki/Euler_diagram

    Euler diagram. An Euler diagram (/ ˈɔɪlər /, OY-lər) is a diagrammatic means of representing sets and their relationships. They are particularly useful for explaining complex hierarchies and overlapping definitions. They are similar to another set diagramming technique, Venn diagrams.

  6. Influence diagram - Wikipedia

    en.wikipedia.org/wiki/Influence_diagram

    An influence diagram (ID) (also called a relevance diagram, decision diagram or a decision network) is a compact graphical and mathematical representation of a decision situation. It is a generalization of a Bayesian network, in which not only probabilistic inference problems but also decision making problems (following the maximum expected ...

  7. Artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Artificial_intelligence

    Artificial intelligence (AI), in its broadest sense, is intelligence exhibited by machines, particularly computer systems.It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals. [1]

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