Showing 4 open source projects for "learning"

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    Tangent

    Tangent

    Source-to-source debuggable derivatives in pure Python

    ...In contrast, Tangent performs ahead-of-time autodiff on the Python source code itself, and produces Python source code as its output. Tangent fills a unique location in the space of machine learning tools. As a result, you can finally read your automatic derivative code just like the rest of your program. Tangent is useful to researchers and students who not only want to write their models in Python, but also read and debug automatically-generated derivative code without sacrificing speed and flexibility. Tangent works on a large and growing subset of Python, provides extra autodiff features other Python ML libraries don't have, has reasonable performance, and is compatible with TensorFlow and NumPy.
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  • 2
    Grevis is a Linux graphical tool for learning and debugging the Perl regular expressions. It uses the output of the regular expression debugger (as of version 5.8.10) to obtain data needed to visualise the matching process step-by-step.
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  • 3
    Dinaao Is Not An Apple One Emulator. It does however already run most apple1 software. It runs on the command line so cut and paste works perfectly. A great 65C02/Basic learning/development environment.
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  • 4
    Mipscope is a cross-platform IDE for students learning assembly on the MIPS architecture. The focus is on a convenient debugging environment, including a visual, reversible debugger.
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