Showing 5 open source projects for "c"

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    XGBoost

    XGBoost

    Scalable and Flexible Gradient Boosting

    ...It also offers parallel tree boosting (GBDT, GBRT or GBM) that can quickly and accurately solve many data science problems. XGBoost can be used for Python, Java, Scala, R, C++ and more. It can run on a single machine, Hadoop, Spark, Dask, Flink and most other distributed environments, and is capable of solving problems beyond billions of examples.
    Downloads: 5 This Week
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  • 2
    DearPyGui

    DearPyGui

    Graphical User Interface Toolkit for Python with minimal dependencies

    ...The Tutorials will provide a great overview and links to each topic in the API Reference for more detailed reading. Complete theme and style control. GPU-based rendering and efficient C/C++ code.
    Downloads: 1 This Week
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  • 3
    MCPower

    MCPower

    MCPower — simple Monte Carlo power analysis for complex models

    MCPower-GUI is a desktop application that provides a graphical interface for the MCPower Monte Carlo power analysis library. It guides users through the full workflow across three tabs: Model setup (formula input with live parsing, CSV data upload with auto-detected variable types, effect size sliders, and correlation editing), Analysis configuration (find power for a given sample size or find the minimum sample size for a target power, with multiple testing correction and scenario...
    Downloads: 0 This Week
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  • 4
    TensorFlow.NET

    TensorFlow.NET

    .NET Standard bindings for Google's TensorFlow for developing models

    ...Since the APIs are kept as similar as possible you can immediately adapt any existing TensorFlow code in C# or F# with a zero learning curve. Take a look at a comparison picture and see how comfortably a TensorFlow/Python script translates into a C# program with TensorFlow.NET.
    Downloads: 0 This Week
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  • 5
    CSAPP-Labs

    CSAPP-Labs

    Solutions and Notes for Labs of Computer Systems

    CSAPP-Labs is a repository that organizes and provides practical lab exercises corresponding to the famous textbook Computer Systems: A Programmer’s Perspective (CS:APP), helping students deepen their understanding of how computer systems work at the machine level. The exercises cover core topics such as data representation, assembly language, processor architecture, cache behavior, memory hierarchy, linking, and concurrency, contextualizing abstract concepts from the book in real code and...
    Downloads: 6 This Week
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