Description

In this bootcamp session, aimed at those new to the field, we will cover an overview of the rapidly-growing field of deep learning.  We will discuss the history of deep learning, the design of architectures for deep learning, training methods, the use of frameworks such as PyTorch for building deep learning models, and applications including audio, vision, and text.  No specific prerequisites are required, though familiarity with coding in languages such as Python is helpful.

Instructor's Bio

Brian Kulis, PhD

Associate Professor at Boston University

Brian Kulis is an associate professor at Boston University, with appointments in the Department of Electrical and Computer Engineering, the Department of Computer Science, the Faculty of Computing and Data Sciences, and the Division of Systems Engineering. From 2019-2023, he was also an Amazon Scholar, and was the inaugural Amazon Scholar for Alexa, where he helped lead long-term research projects at Alexa.  He obtained his PhD in computer science from the University of Texas in 2008, and his BA degree from Cornell University in computer science and mathematics in 2003. For his research, he has won three best paper awards at top-tier conferences---two at the International Conference on Machine Learning (in 2005 and 2007) and one at the IEEE Conference on Computer Vision and Pattern Recognition (in 2008).  He was also the recipient of an NSF CAREER Award in 2015, and was named an AIMiner Top 100 Most Influential Scholars in Machine Learning in 2019.

Webinar

UPCOMING LIVE TRAINING

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