Renormalization & ScalingExplores renormalization, scaling, critical points, exponents, and phase transitions in conformal field theory and quantum gravity.
PCA: Key ConceptsCovers the key concepts of Principal Component Analysis (PCA) and its practical applications in data dimensionality reduction and feature extraction.
PCA: Key ConceptsCovers the key concepts of PCA, including reducing data dimensionality and extracting features, with practical exercises.
Multivariate Methods IExplores multivariate methods like PCA, SVD, PLS, and ICA for dimensionality reduction in functional brain imaging.
Market Response FunctionsExplores market response functions, flash crashes, correlation estimation, and noise filtering in finance.
Linearisation of FlowCovers the linearization of flow around a point, eigenvalues, eigenvectors, and critical points.
Diagonalization of MatricesExplores the diagonalization of matrices through eigenvalues and eigenvectors, emphasizing the importance of bases and subspaces.
Eigenvalues and EigenvectorsExplores eigenvalues, eigenvectors, and methods for solving linear systems with a focus on rounding errors and preconditioning matrices.
Calcul de valeurs propresCovers the calculation of eigenvalues and eigenvectors, emphasizing their significance and applications.
