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  2. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    OpenML: [493] Web platform with Python, R, Java, and other APIs for downloading hundreds of machine learning datasets, evaluating algorithms on datasets, and benchmarking algorithm performance against dozens of other algorithms. PMLB: [494] A large, curated repository of benchmark datasets for evaluating supervised machine learning algorithms ...

  3. 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]

  4. Category:Machine learning algorithms - Wikipedia

    en.wikipedia.org/wiki/Category:Machine_learning...

    Category: Machine learning algorithms. ... Download QR code; Print/export Download as PDF; Printable version; In other projects Wikimedia Commons;

  5. Category:Machine learning - Wikipedia

    en.wikipedia.org/wiki/Category:Machine_learning

    Machine learning is a branch of statistics and computer science which studies algorithms and architectures that learn from observed facts. The main article for this category is Machine learning . Wikimedia Commons has media related to Machine learning .

  6. Outline of machine learning - Wikipedia

    en.wikipedia.org/wiki/Outline_of_machine_learning

    Machine learning (ML) is a subfield of artificial intelligence within computer science that evolved from the study of pattern recognition and computational learning theory. [1] In 1959, Arthur Samuel defined machine learning as a "field of study that gives computers the ability to learn without being explicitly programmed". [ 2 ]

  7. Computational learning theory - Wikipedia

    en.wikipedia.org/wiki/Computational_learning_theory

    Online machine learning, from the work of Nick Littlestone [citation needed]. While its primary goal is to understand learning abstractly, computational learning theory has led to the development of practical algorithms. For example, PAC theory inspired boosting, VC theory led to support vector machines, and Bayesian inference led to belief ...

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  9. Learning classifier system - Wikipedia

    en.wikipedia.org/wiki/Learning_classifier_system

    A step-wise schematic illustrating a generic Michigan-style learning classifier system learning cycle performing supervised learning. Keeping in mind that LCS is a paradigm for genetic-based machine learning rather than a specific method, the following outlines key elements of a generic, modern (i.e. post-XCS) LCS algorithm.

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