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Teachings

I currently work as a teaching assistant at ENSAE IP Paris for Xavier Dupré’s Python pour le Data Scientist.

This course is an introductory course to machine learning and includes a lot of lab sessions with python and scikit-learn.

The outline of the lab sessions is the following :

TP1 : ML basics, classification, classification metrics. Notebook
TP2 : Regression, regression metrics, trees, random forests. Notebook
TP3 : Cross validation, boosting, hyperparameter tuning Notebook
TP4 : Deep learning basics and introduction to natural language processing with Keras. Notebook

The complete github repository containing the .ipynb files can be found here.

I gave this course during February 2020 at Université Gustave Eiffel. A short syllabus can be found here

I gave a refined version of this course for Etienne Ollion at Ecole Polytechnique