Catalog Description
Recently Deep Learning (DL) techniques have shown a lot of promise for tasks in various modalities such as speech, language, and vision and DL has become a go-to machine learning paradigm for Artificial Intelligence (AI) based applications. The course aims to cover theoretical and applied aspects of Deep Learning and how it is used to solve real-world problems. Classes in each week may be divided into two segments: (a) Theory and Methods, a concise description of a deep learning algorithm, and (b) Lab Tutorial, a hands-on session on applying the algorithm on multimodal real world data such as textual, visual and audio data.
Prerequisites
Graduate standing.