## Dimension Reduction

Responsible of 24-hour lecture in Master of Machine Learning

During my PhD, I have the opportunity to teach at University of Lille. I was lucky to get a Master course, with the freedom to design lectures and tutorials.

Part of a computer science Degree specialized in Machine Learning, I aim to give students a better intuition of high dimension, and of the trade-off between dimension reduction and preservation of data characteristics. The goal is also to strengthen their mathematical background and their ability to code in Python. The lecture covers the curse of dimensionality, PCA, SVD, kernel-PCA, manifold-learning, LLE, t-SNE, spectral clustering…