Spring 2025

INF 385T Special Topics in Information Science: Deep Learning and Multimodal Systems

Unique ID: 28440

   Tues

09:30 AM - 12:30 PM  UTA 1.210A

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.

RESTRICTIONS

Restricted to graduate students in the School of Information through registration periods 1 and 2. Outside students will be permitted to join our waitlists beginning in registration period 3.