A python, pure software design pattern based package that features several tutorial in order to showcase basic, cross-platform scientific computing and OpenGL-based real-time computer graphics with applications to scientific visualization and deep learning.
Copyright 2021-2022 Dr. George Papagiannakis, papagian@csd.uoc.gr
Why EEL?:
This package is aimed as a basic behind-the-black-box implementation of several classic as well as modern scientific computing, computer graphics, deep learning and geometric algebra methodologies, algorithms and techniques, aimed for teaching as well as a framework/playgrounf for novel research.
It contains the following sections of tutorials as jupyter notebooks:
- SciCom: Scientific Computing with python
- GATE: Geometric Algebra Transformation Engine
- DL: Deep Learning
- CG: Computer Graphics
- neuralCG: deep learning 4 computer graphics
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For
development: viagithubgit clone .......and in order to install it
locallyviapip:python -m pip install -e .
- Prof. George Papagiannakis
- Dr. Kamarianakis Manos
pyEEL is licensed under the Apache License, Version 2.0. See LICENSE.txt for the full license text.