3 projects for "python programming language" with 2 filters applied:

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  • 1
    polynote

    polynote

    A better notebook for Scala (and more)

    Polynote is an innovative polyglot notebook environment that improves on traditional interactive computing tools by enabling multi-language notebooks where users can mix languages like Scala, Python, SQL, and more within a single document while sharing variables and definitions seamlessly across those languages. Designed to address shortcomings in classic notebook solutions, it blends features familiar from IDEs β€” such as smart autocomplete, parameter hints, and better runtime insights β€” with the flexibility of notebook workflows, enhancing both developer productivity and data exploration. ...
    Downloads: 0 This Week
    Last Update:
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  • 2
    QA-Pilot

    QA-Pilot

    QA-Pilot is an interactive chat project that leverages LLMs

    QA-Pilot is an interactive chat-based application designed to help users understand and navigate GitHub repositories using large language models. It enables users to clone repositories locally and then interact with them through a conversational interface, allowing for rapid exploration of codebases without manual searching. The system supports both local and cloud-based LLM providers, making it flexible for different environments and privacy requirements. It includes features such as chat...
    Downloads: 5 This Week
    Last Update:
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  • 3
    Super comprehensive deep learning notes

    Super comprehensive deep learning notes

    Super Comprehensive Deep Learning Notes

    Super comprehensive deep learning notes is a massive and well-structured collection of deep learning notebooks that serve as a comprehensive study resource for anyone wanting to learn or reinforce concepts in computer vision, natural language processing, deep learning architectures, and even large-model agents. The repository contains hundreds of Jupyter notebooks that are richly annotated and organized by topic, progressing from basic Python and PyTorch fundamentals to advanced neural network designs like ResNet, transformers, and object detection algorithms. It’s not just a dry code repository; it includes theoretical explanations alongside hands-on examples, loss function explorations, optimization routines, and full end-to-end experiments on real datasets, making it highly suitable for both self-study and classroom use.
    Downloads: 0 This Week
    Last Update:
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