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  2. Probably approximately correct learning - Wikipedia

    en.wikipedia.org/wiki/Probably_approximately...

    e. In computational learning theory, probably approximately correct (PAC) learning is a framework for mathematical analysis of machine learning. It was proposed in 1984 by Leslie Valiant. [1] In this framework, the learner receives samples and must select a generalization function (called the hypothesis) from a certain class of possible functions.

  3. scikit-learn - Wikipedia

    en.wikipedia.org/wiki/Scikit-learn

    scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...

  4. Missionaries and cannibals problem - Wikipedia

    en.wikipedia.org/wiki/Missionaries_and_cannibals...

    The missionaries and cannibals problem, and the closely related jealous husbands problem, are classic river-crossing logic puzzles. [1] The missionaries and cannibals problem is a well-known toy problem in artificial intelligence, where it was used by Saul Amarel as an example of problem representation. [2][3]

  5. Python (programming language) - Wikipedia

    en.wikipedia.org/wiki/Python_(programming_language)

    Python is a multi-paradigm programming language. Object-oriented programming and structured programming are fully supported, and many of their features support functional programming and aspect-oriented programming (including metaprogramming [ 70 ] and metaobjects). [ 71 ] Many other paradigms are supported via extensions, including design by ...

  6. History of Python - Wikipedia

    en.wikipedia.org/wiki/History_of_Python

    Python 2.6 was released to coincide with Python 3.0, and included some features from that release, as well as a "warnings" mode that highlighted the use of features that were removed in Python 3.0. [ 27 ] [ 10 ] Similarly, Python 2.7 coincided with and included features from Python 3.1, [ 28 ] which was released on June 26, 2009.

  7. Machine learning - Wikipedia

    en.wikipedia.org/wiki/Machine_learning

    Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. [ 1 ]

  8. Constraint satisfaction - Wikipedia

    en.wikipedia.org/wiki/Constraint_satisfaction

    Constraint satisfaction. In artificial intelligence and operations research, constraint satisfaction is the process of finding a solution through a set of constraints that impose conditions that the variables must satisfy. [1] A solution is therefore an assignment of values to the variables that satisfies all constraints—that is, a point in ...

  9. Description logic - Wikipedia

    en.wikipedia.org/wiki/Description_logic

    A description logic (DL) models concepts, roles and individuals, and their relationships. The fundamental modeling concept of a DL is the axiom —a logical statement relating roles and/or concepts. [2] This is a key difference from the frames paradigm where a frame specification declares and completely defines a class.