Showing 4 open source projects for "machine learning projects"

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  • 1
    ALCHA

    ALCHA

    A New Programming Language for FPGA Projects

    ALCHA aims to reduce FPGA project develop time by means of automation and abstraction, but without loosing the low-level control that HDLs, such as Verilog, provides. It will support an object oriented programming model, abstract data and signal types, and compile-time scripting.
    Downloads: 0 This Week
    Last Update:
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  • 2
    RE/flex lexical analyzer generator

    RE/flex lexical analyzer generator

    The regex-centric, fast lexical analyzer generator for C++

    A C++ high-performance regex library and Flex-compatible lexical analyzer generator with full Unicode support, new indentation anchors, lazy quantifiers, and many other modern features. Accepts Flex lexer specification syntax and is compatible with Bison/Yacc parsers. Generates reusable source code that is easy to understand. Supports fast scanning of UTF-8/16/32 files, strings, and streams. The reflex scanner generator generates clean C++ lexer class code that is thread-safe. Generates...
    5.0 out of 5 stars 2 Reviews
    Downloads: 24 This Week
    Last Update:
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  • 3
    Tabnine

    Tabnine

    Vim client for TabNine

    ...Whether you call it IntelliSense, intelliCode, autocomplete, AI-assisted code completion, AI-powered code completion, AI copilot, AI code snippets, code suggestion, code prediction, code hinting, or content assist, you probably already know that it can save you tons of time, easily cutting your keystrokes in half. Powered by sophisticated machine learning models trained on billions of lines of trusted open source code from GitHub, Tabnine is the most advanced AI-powered code completion copilot available today. And like GitHub, it is an essential tool for professional developers.
    Downloads: 21 This Week
    Last Update:
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  • 4
    pyIRDG

    pyIRDG

    IMDb Relational Dataset Generator

    pyIRDG is a program written in Python to generate relational datasets in Prolog format. It uses data from the Internet Movie Database in combination with IMDbPY as backend. A graphical user interface written in pyQt allows the user to link multiple entities together as model for the generation process. The big four entities are Title, Person, Company and Character. Many attributes can be chosen for adding to the output .pl file. Three types of constraints on attributes are available to limit...
    Downloads: 0 This Week
    Last Update:
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