This online workshop will provide the requisite background for training deep learning models in PyTorch. First, we will build a neural network from scratch and discuss back-propagation. Second, we will discuss how to load custom data sets for training. Finally, you will train a neural network on the classic MNIST data set.
Prerequisite: You should be comfortable with Python, Pandas, and Numpy.
This workshop is part of our Coding Is for Everyone Series.
Date:
Thursday, November 12, 2020
Presenter:
Barry Moore II (Center for Research Computing)
Categories:
Digital Scholarship Workshop/Presentation, Workshops