Deep Learning in Pytorch

Instructor

• Instructor: D. Hudson Smith

• Office: 2105 Barre Hall, Clemson University

• Email: dane2 AT clemson DOT edu

Workshop Description

This workshop series introduces the essential concepts in deep learning and walks through the common steps in a deep learning workflow from data loading and preprocessing to training and model evaluation. Throughout the sessions, students participate in writing and executing simple deep learning programs using Pytorch – a popular Python library for developing, training, and deploying deep learning models.

Prerequisites

All students should have a Palmetto Cluster account. If you do not already have an account, you can visit our getting started page. Students should be familiar with the Python programming language. This requirement could be fulfilled by personal projects, coursework, or completion of the Introduction to Python Programming workshop series. Experience in numeric computing with the numpy library is helpful but not required.