ML Project/Data science

Crédit : 5 ECTS
Langue du cours : anglais

Volume horaire

• CM : 36 h
• Volume horaire global (hors stage) : 36 h

Compétences à acquérir

Implement common Machine Learning techniques in Python (with the help of the libraries NumPy, Pandas and scikit learn).

Description du contenu de l'enseignement

Project: work by groups of two, build or use an existing (real) dataset, process the dataset by using the methods presented in the courses. Implement the different methods presented in the Machine Learning course by using the libraries NumPy, Pandas and scikit-learn on real or synthetic data:

• k-nearest neighbors (k-NNs);
• Linear/Quadratic Discriminant Analysis (LDA/QDA);
• Logistic regression;
• Clustering: k-means, agglomerative clustering;
• Decision tree learning, random forests;
• Neural networks.

Mode de contrôle des connaissances

Graded tutorial (TP noté) + Project.

Pré-requis obligatoires

Programming language: Python.

Enseignant responsable

PIERRE WOLINSKI