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  2. List of programming languages for artificial intelligence

    en.wikipedia.org/wiki/List_of_programming...

    C# can be used to develop high level machine learning models using Microsoft’s .NET suite. ML.NET was developed to aid integration with existing .NET projects, simplifying the process for existing software using the .NET platform. Smalltalk has been used extensively for simulations, neural networks, machine learning, and genetic algorithms.

  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. Retrieval-augmented generation - Wikipedia

    en.wikipedia.org/wiki/Retrieval-augmented_generation

    Retrieval-augmented generation (RAG) is a technique that enables generative artificial intelligence (Gen AI) models to retrieve and incorporate new information. [1] It modifies interactions with a large language model (LLM) so that the model responds to user queries with reference to a specified set of documents, using this information to supplement information from its pre-existing training ...

  5. Symbolic regression - Wikipedia

    en.wikipedia.org/wiki/Symbolic_regression

    QLattice is a quantum-inspired simulation and machine learning technology that helps search through an infinite list of potential mathematical models to solve a problem. [13] [14] Evolutionary Forest is a Genetic Programming-based automated feature construction algorithm for symbolic regression. [15] [16]

  6. Physics-informed neural networks - Wikipedia

    en.wikipedia.org/wiki/Physics-informed_neural...

    Physics-informed neural networks for solving Navier–Stokes equations. Physics-informed neural networks (PINNs), [1] also referred to as Theory-Trained Neural Networks (TTNs), [2] are a type of universal function approximators that can embed the knowledge of any physical laws that govern a given data-set in the learning process, and can be described by partial differential equations (PDEs).

  7. 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).

  8. OCaml - Wikipedia

    en.wikipedia.org/wiki/OCaml

    The OCaml 4.0 release in 2012 added Generalized Algebraic Data Types (GADTs) and first-class modules to increase the flexibility of the language. [11] The OCaml 5.0.0 release in 2022 [ 13 ] is a complete rewrite of the language runtime, removing the global GC lock and adding effect handlers via delimited continuations .

  9. Non-English-based programming languages - Wikipedia

    en.wikipedia.org/wiki/Non-English-based...

    bato on GitHub: Tamil: Ezhil: Developed for educational purposes. eTamil The purpose of eTamil is to be an Indian DSL for Accounts & Fintech. eTamil on GitHub: Swaram A simple, general-purpose and procedural language. [21] Agaram A simple, Tamil programming language with interpreter and compiler. Agaram-programming-language on GitHub: Niral