Metadata-Version: 2.1
Name: mlgeo
Version: 0.0.3
Summary: Repository for Machine Learning in Geotechnics
Home-page: https://github.com/groundworkai/mlgeo
Author: Nick Machairas
Author-email: nick@groundwork.ai
License: UNKNOWN
Description: # Repository for Machine Learning in Geotechnics
        
        <div style="text-align:center;">
            <img src="https://img.shields.io/badge/Python-3.7%2B-brightgreen" alt="Python version">
            <a href="https://pypi.org/project/mlgeo" target="_blank">
                <img src="https://img.shields.io/pypi/v/mlgeo?style=flat&color=brightgreen&label=PyPI%20Package" alt="Package version">
            </a>
            <br><br>
        </div>
        
        
        This is the beginning of an exciting effort in lowering the barrier of entry to 
        Machine Learning for Geoprofessionals by:
        
        1. Distributing relevant and interesting toy datasets to practice with (now)
        2. Offering tools that can make applying ML easier, especially for beginners (soon)
        
        
        ### TRB2021 AKG70 Presentation
        
        Click on the image below to review the presentation introducing MLgeo given by 
        [Nick Machairas](https://groundwork.ai/nickmachairas) during the committee 
        meeting of AKG70 at TRB Annual Meeting 2021.
        
        <a href="https://docs.google.com/presentation/d/e/2PACX-1vSY3gSpaS7dOQrtrwouNKZKm000_uMI1CmtuR94HZ9tR_54U7C3IGHaRDbe9QE2V6xUCBPYMx2iD7Xc/pub?start=false&loop=false&delayms=3000">
            <img src="https://storage.googleapis.com/mlgeo/TRB2021_Presentation_Cover_MLgeo.jpg" alt="TRB Presentation">
        </a>
        
        
        ---
        
        <div>
            <h3><img src="https://mirrors.creativecommons.org/presskit/buttons/88x31/png/by-sa.png" alt="CC-BY-SA-4.0" height="30px"><br>License: Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
            </h3>
            <p>
                You are free to <strong>Share</strong> (copy and redistribute the material 
                in any medium or format) and <strong>Adapt</strong> (remix, transform, and 
                build upon the material for any purpose, even commercially), under the 
                following terms: <strong>Attribution</strong> — You must give appropriate 
                credit, provide a link to the license, and indicate if changes were made. 
                You may do so in any reasonable manner, but not in any way that suggests 
                the licensor endorses you or your use. <strong>ShareAlike</strong> — If 
                you remix, transform, or build upon the material, you must distribute 
                your contributions under the same license as the original. More details 
                <a href="https://creativecommons.org/licenses/by-sa/4.0/">here</a>.
            </p>
        </div>
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: Other/Proprietary License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
