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

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

    Most data files are adapted from UCI Machine Learning Repository data, some are collected from the literature. treated for missing values, numerical attributes only, different percentages of anomalies, labels 1000+ files ARFF: Anomaly detection: 2016 (possibly updated with new datasets and/or results) [331] Campos et al.

  3. Orange (software) - Wikipedia

    en.wikipedia.org/wiki/Orange_(software)

    Orange is an open-source software package released under GPL and hosted on GitHub.Versions up to 3.0 include core components in C++ with wrappers in Python.From version 3.0 onwards, Orange uses common Python open-source libraries for scientific computing, such as numpy, scipy and scikit-learn, while its graphical user interface operates within the cross-platform Qt framework.

  4. C Sharp (programming language) - Wikipedia

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

    Four years later, in 2004, a free and open-source project called Microsoft Mono began, providing a cross-platform compiler and runtime environment for the C# programming language. A decade later, Microsoft released Visual Studio Code (code editor), Roslyn (compiler), and the unified .NET platform (software framework), all of which support C# ...

  5. Machine learning - Wikipedia

    en.wikipedia.org/wiki/Machine_learning

    Machine learning and data mining often employ the same methods and overlap significantly, but while machine learning focuses on prediction, based on known properties learned from the training data, data mining focuses on the discovery of (previously) unknown properties in the data (this is the analysis step of knowledge discovery in databases).

  6. Julia (programming language) - Wikipedia

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

    Julia is a high-level, general-purpose [17] dynamic programming language, designed to be fast and productive, [18] for e.g. data science, artificial intelligence, machine learning, modeling and simulation, most commonly used for numerical analysis and computational science. [19] [20] [21]

  7. Data science - Wikipedia

    en.wikipedia.org/wiki/Data_science

    Data science is multifaceted and can be described as a science, a research paradigm, a research method, a discipline, a workflow, and a profession. [4] Data science is "a concept to unify statistics, data analysis, informatics, and their related methods" to "understand and analyze actual phenomena" with data. [5]

  8. Active learning (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Active_learning_(machine...

    Active learning is a special case of machine learning in which a learning algorithm can interactively query a human user (or some other information source), to label new data points with the desired outputs. The human user must possess knowledge/expertise in the problem domain, including the ability to consult/research authoritative sources ...

  9. Generative artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Generative_AI

    Large language model – Type of machine learning model; Music and artificial intelligence – Usage of artificial intelligence to generate music; Generative AI pornography – Explicit material produced by generative AI; Procedural generation – Method in which data is created algorithmically as opposed to manually