myrs 0.0.2
The friendly scientific machine learning library
License: new BSD
Requires Python: >=3.11,<4.0

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    <h1 style="font-size: 30px; margin-bottom: 10px;">💧 Myrs</h1>
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    <p style="font-size: 20px; font-weight: bold; color: #000;">The <span style="color: #00B7FF;">friendly</span> scientific machine learning library</p>
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    <p style="font-weight: bold; background-color: #0074d9; padding: 5px;"> ⁉️ ABOUT</p>
    <p><strong>Myrs</strong> is an attempt to provide a <strong>high-level</strong> and <strong>human</strong> friendly <a href="https://en.wikipedia.org/wiki/API">API</a> for <strong>Scientific Machine Learning</strong> algorithms such as <a href="https://arxiv.org/abs/2201.05624">PINN</a>, <a href="https://arxiv.org/abs/1909.09586">LSTM-RNN</a>, <a href="https://arxiv.org/abs/2307.15092">RC</a>... but with <strong>applications</strong> in mind.</p>
    <p>In fact, in the same way as <a href="https://scikit-learn.org/stable/index.html">scikit-learn</a>, the user will find the algorithms classified by <strong>applications</strong> and practical use-cases in <strong>science</strong> and <strong>engineering</strong>.</p>
    <p>Although some implementations and packages already exist, the Python Scientific Machine Learning Community is <strong>sparse</strong>... Thus, the <strong>long-term</strong> goal of the project is to provide a <strong>constitutive</strong> implementation of such algorithms under the same <strong>banner</strong>.</p>
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    <p style="font-weight: bold; background-color: #ff851b; padding: 5px;">🎯 GOALS</p>
    <ul>
        <li>Satisfy my <strong>willingness</strong> to <strong>deep dive</strong> into <strong>Scientific Machine Learning</strong> algorithms</li>
        <li>Be <strong>useful</strong>... (a hard goal 😅)</li>
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    <p style="font-weight: bold;background-color: #2ecc40; padding: 5px;">🚀 FEATURES</p>
    <ul>
        <li><strong>Simple</strong> and <strong>efficient</strong> tools for solving <strong>science</strong> and <strong>engineering</strong> problems using <strong>Machine Learning</strong></li>
        <li><strong>Practical</strong> and <strong>expressive</strong> API</li>
        <li>Stand on the <strong>shoulders of giants</strong> -> on top of <a href="https://pandas.pydata.org/">Pandas</a>, <a href="https://keras.io/">Keras</a>, <a href="https://scikit-learn.org/stable/">scikit-learn</a> and <a href="https://seaborn.pydata.org/">seaborn</a> 
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    <p style="font-weight: bold;background-color: #ff4136; padding: 5px;">⚠️ WARNINGS</p>
    <p><strong>For the moment:</strong></p>
    <ul>
        <li>The development of the project takes place in a <strong>private</strong> GitHub repository</li>
        <li>The project is at a very <strong>early stage</strong> -> <strong>Nothing</strong> is implemented in this <strong>published version</strong></li>
        <li>The <strong>documentation</strong> is <strong>missing</strong></li>
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    <p>The <strong>GitHub repository</strong> as well as a <strong>usable</strong> Python package will be<strong> available</strong> in the <strong>upcoming months</strong>, when the project will be <strong>more advanced</strong>.</p>

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    <p style="font-weight: bold;background-color: #AD90FF; padding: 5px;">🤝 COMMUNITY-DRIVEN</p>
    <p><strong>Myrs</strong> is foremost a <strong>community-driven</strong> project! The project will be <strong>highly collaborative</strong>, so everyone is welcome to the project! 🤗 <p>
    <p>Don't hesitate to contact me if you want to know more or are interested in ! 😃</p>
    <strong>Stay tuned !</strong> 🗓️
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