Program (detailed contents):
– Introduction to exploratory data analysis
– Syntax and objects of R and Python languages, functions, object and functional programmation (Python).
– Factorial methods. Reminder on principal component analysis (PCA). Variants of PCA for qualitative data (correspondence analysis), classification (linear discriminant analysis), distance-based data (multidimensional scaling), non-linearities (kernel PCA)
– Clustering: reminder on basic techniques (k-means, hierarchical clustering). Mixture models and EM algorithm. Community slicing or graph clustering.
– Non-négative matrix factorization (NMF) and introduction to recommendation.
