In this webinar, you will learn the concept of dimension reduction and how to use PCA, t-SNE and UMAP as 3 widely used dimension reduction methods.
The focus of the webinar is helping you to understand the assumptions and intuition behind each dimension reduction approaches (mainly ) and how to use Python to implement these methods for feature selection or visualization.
Ali is currently a Ph.D. candidate at the University of Toronto working on the development of new machine learning models to predict cancer patients responses to drugs. During his study, he published research papers in high impact scientific journals and international conferences covering such fields as ensemble learning, and unsupervised clustering. He has earned a master of a mathematics degree, focusing on modeling of stochastic processes in complex biological systems from the University of Waterloo