Machine learning models can largely outperform classical algorithms to make predictions about complexe problems, e.g. recognizing trees (which can vary a lot depending on the season, the species…). To do so, they learn from data (either from examples or experience) instead of following a well-defined sequence of instructions (like a cooking recipe). We humans do the same to teach our kids to recognize trees: we do not provide instructions but examples.

Python 3.6 or above is required. You can install by Via PyPI, Via GitHub for the latest development version or Development installation.

Step by step installation of GEMS-AI package




Code source on GitHub

You can find onGitHub : theIntroduction, Installation guide, User guide (Measuring model influence, Evaluating model reliability, Support for image classification), Authors and License.


This work is done at the Toulouse Mathematics Institute. It is supported by the Centre National de la Recherche Scientifique (CNRS) and in collaboration with the Artificial and Natural  Intelligence Toulouse



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