This is an undergraduate course (in French!) introducing Python for scientific computing.
We will address some of the element in the Python scientific ecosystem:
Syllabus
Course note
Introduction à Python, version 2020-2021 (under construction)
Cours: slides et notebooks
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IntroPython_slides.pdf, prise_en_main_notebook.ipynb, prise_en_main_notebook.html
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pandas_slides.pdf, pandas.ipynb, pandas.html, belgianmunicipalities.ipynb, belgianmunicipalities.html
Travaux pratiques
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TP1-Introduction.pdf, TP1-Introduction-skeleton.ipynb,TP1-Introduction.html, TP1-Introduction.ipynb,
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TP2-boucles_functions.pdf, TP2-boucles_functions-skeleton.ipynb, TP2-boucles_functions.ipynb, TP2-boucles_functions.html
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TP3-numpy_matplolib.pdf, TP3-numpy_matplolib-skeleton.ipynb, TP3-numpy_matplolib-skeleton.html, TP3-numpy_matplolib.ipynb, TP3-numpy_matplolib.html
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TP4-descente_gradient.pdf, TP4-descente_gradient-skeleton.ipynb,
More resources
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Jake VanderPlas book on datascience and associated videos
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sklearn: example of git https://github.com/scikit-learn/scikit-learn and example of diff https://github.com/scikit-learn/scikit-learn/commit/19eb458567fec216584015c1156d6451d949f2de