Showing 5 open source projects for "visual basic documentation generator"

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  • Rezku Point of Sale Icon
    Rezku Point of Sale

    Designed for Real-World Restaurant Operations

    Rezku is an all-inclusive ordering platform and management solution for all types of restaurant and bar concepts. You can now get a fully custom branded downloadable smartphone ordering app for your restaurant exclusively from Rezku.
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  • Simplify Purchasing For Your Business Icon
    Simplify Purchasing For Your Business

    Manage what you buy and how you buy it with Order.co, so you have control over your time and money spent.

    Simplify every aspect of buying for your business in Order.co. From sourcing products to scaling purchasing across locations to automating your AP and approvals workstreams, Order.co is the platform of choice for growing businesses.
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  • 1
    DeepWiki Open

    DeepWiki Open

    AI-Powered Wiki Generator for GitHub/Gitlab/Bitbucket Repositories

    DeepWiki Open is an open-source, AI-powered wiki generator that automatically creates fully navigable, richly structured wiki documentation for GitHub, GitLab, or Bitbucket repositories by combining code analysis, vector embeddings, retrieval-augmented generation (RAG), and visualization tools. Users can enter a repository URL and the system will clone the project, build semantic embeddings of its codebase, extract architecture and relationships, generate human-readable documentation, and produce visual diagrams to help explain complex code structure. ...
    Downloads: 0 This Week
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  • 2
    Learning Interpretability Tool

    Learning Interpretability Tool

    Interactively analyze ML models to understand their behavior

    The Learning Interpretability Tool (LIT, formerly known as the Language Interpretability Tool) is a visual, interactive ML model-understanding tool that supports text, image, and tabular data. It can be run as a standalone server, or inside of notebook environments such as Colab, Jupyter, and Google Cloud Vertex AI notebooks.
    Downloads: 7 This Week
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  • 3
    Machine Learning Glossary

    Machine Learning Glossary

    Machine learning glossary

    Machine Learning Glossary is an open educational project that provides clear explanations of machine learning terminology and concepts through visual diagrams and concise definitions. The goal of the repository is to make machine learning topics easier to understand by presenting definitions alongside examples, visual illustrations, and references for further learning. It covers a wide range of topics including neural networks, regression models, optimization techniques, loss functions, and...
    Downloads: 0 This Week
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  • 4
    NASH OS

    NASH OS

    Nash Operating System for Modern Ecommerce

    The all-built-in-one, automatic, ready-to-go out-of-box, easy-to-use state-of-the-art, and really awesome NASH OS! Over 25,000+ flexible features and controls and all scalable!! The most powerful solution ever built to instantly deliver new heights of online ecommerce enterprise to you.
    Downloads: 2 This Week
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  • Next-Gen Encryption for Post-Quantum Security | CLEAR by Quantum Knight Icon
    Next-Gen Encryption for Post-Quantum Security | CLEAR by Quantum Knight

    Lock Down Any Resource, Anywhere, Anytime

    CLEAR by Quantum Knight is a FIPS-140-3 validated encryption SDK engineered for enterprises requiring top-tier security. Offering robust post-quantum cryptography, CLEAR secures files, streaming media, databases, and networks with ease across over 30 modern platforms. Its compact design, smaller than a single smartphone image, ensures maximum efficiency and low energy consumption.
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  • 5

    NeuroSolutions: Formula Generator

    Utility converts the weights file of a MLP Breadboard into a formula

    The NeuroSolutions: Formula Generator utility converts the weights file of a default MLP breadboard (1-hidden layer with a TanhAxon in the hidden layer and either a TanhAxon or BiasAxon in the output layer) into a usable formula that can be copied and pasted into your own programs to compute the output of the trained neural network.
    Downloads: 0 This Week
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