Numerical Tours

of Data Science

Welcome to the Numerical Tours of Data Science

The Numerical Tours of Data Science, by Gabriel Peyré, gather Matlab, Python and Julia experiments to explore modern mathematical data science. They cover data science in a broad since, including imaging, machine learning, computer vision and computer graphics. It showcases application of numerical and mathematical methods such as convex optimization, PDEs, optimal transport, inverse problems, sparsity, etc. The tours are complemented by slides of courses detailing the theory and the algorithms.

Numerical Tours on Machine Learning

4 new Matlab tours

Numerical Tours now in Julia

30 Julia tours available

Numerical Tours now in Python

30 Python tours available

New Python Tours

Optimization by Laurent Condat

Updated tour

Entropic Regularization of Optimal Transport