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  2. List of artificial intelligence projects - Wikipedia

    en.wikipedia.org/wiki/List_of_artificial...

    OpenCog, a GPL-licensed framework for artificial intelligence written in C++, Python and Scheme. [15] PolyAnalyst: A commercial tool for data mining, text mining, and knowledge management. [89] RapidMiner, an environment for machine learning and data mining, now developed commercially. [90]

  3. List of Apache Software Foundation projects - Wikipedia

    en.wikipedia.org/wiki/List_of_Apache_Software...

    MADlib: Scalable, Big Data, SQL-driven machine learning framework for Data Scientists; Mahout: machine learning and data mining solution. Mahout; ManifoldCF: Open-source software for transferring content between repositories or search indexes; Maven: Java project management and comprehension tool

  4. Data-driven model - Wikipedia

    en.wikipedia.org/wiki/Data-driven_model

    Data-driven models encompass a wide range of techniques and methodologies that aim to intelligently process and analyse large datasets. Examples include fuzzy logic, fuzzy and rough sets for handling uncertainty, [3] neural networks for approximating functions, [4] global optimization and evolutionary computing, [5] statistical learning theory, [6] and Bayesian methods. [7]

  5. Weka (software) - Wikipedia

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

    Environment for DeveLoping KDD-Applications Supported by Index-Structures is a similar project to Weka with a focus on cluster analysis, i.e., unsupervised methods. H2O.ai is an open-source data science and machine learning platform; KNIME is a machine learning and data mining software implemented in Java.

  6. Open-source artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Open-source_artificial...

    Open-source artificial intelligence is an AI system that is freely available to use, study, modify, and share. [1] These attributes extend to each of the system's components, including datasets, code, and model parameters, promoting a collaborative and transparent approach to AI development. [1]

  7. Predictive analytics - Wikipedia

    en.wikipedia.org/wiki/Predictive_analytics

    Predictive analytics statistical techniques include data modeling, machine learning, AI, deep learning algorithms and data mining. Often the unknown event of interest is in the future, but predictive analytics can be applied to any type of unknown whether it be in the past, present or future.

  8. Category:Machine learning - Wikipedia

    en.wikipedia.org/wiki/Category:Machine_learning

    Data augmentation; Data exploration; Data preprocessing; Data-driven astronomy; Data-driven model; Decision list; Decision tree pruning; Developmental robotics; Digital signal processing and machine learning; Discovery system (AI research) Document classification; Domain adaptation; Double descent

  9. Applications of artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Applications_of_artificial...

    AI driven tutoring systems, such as Khan Academy, Duolingo and Carnegie Learning are the forefoot of delivering personalized education. [58] These platforms leverage AI algorithms to analyze individual learning patterns, strengths, and weaknesses, enabling the customization of content and Algorithm to suit each student's pace and style of learning.

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