Deep Learning: A Hands-on Introduction

1 Course Unit

This course will serve as an introductory and hands-on dive into the area of deep learning. The main goal is to to educate the students on (i) the commonly-used neural network architectures and proficiency in training them, (ii) Some of the main problems that deep learning systems have successfully addressed (formulation, architecture, data sets, etc). There will be no theory in this course. After finishing this course, the students should be very comfortable with pytorch programming as well as training deep learning models. Fall Prerequisites: Students must take ESE 2000 OR CIS 4210 before taking ESE 3060. 1 Course Unit