About Event

In this course we intend to introduce the basic concepts of computer vision and machine learning from a mathematically well motivated perspective. This course covers some of the most popular supervised learning algorithms including linear regression, decision trees, k-nearest neighbor, Bayesian learning, support vector machines, neural networks with an introduction to Deep Learning and unsupervised clustering algorithms. We also discuss about, how machine learning algorithms are applied to various computer vision problems. This course also includes hands-on problem solving with programming in Python and some tutorial sessions. Eminent resource persons will be handling the sessions.