Computer Vision for the Humanities: An Introduction to Deep Learning for Image Classification (Part 1)
Resource type
External Resource
Authors, editors and contributors
Daniel van Strien, Kaspar Beelen, Melvin Wevers, Thomas Smits, Katherine McDonough, Nabeel Siddiqui, Alex Wermer-Colan, Michael Black, Catherine DeRose
Topics (keywords)
DH, Open Education, Open Access, Python, Machine learning
Learning outcomes
After completing this lesson, you will have learned:
What steps are needed to train a deep learning model
To understand some of the specific considerations around using deep learning and computer vision for humanities research
Abstract
This is the first of a two-part lesson introducing deep learning based computer vision methods for humanities research. Using a dataset of historical newspaper advertisements and the fastai Python library, the lesson walks through the pipeline of training a computer vision model to perform image classification.
Title of the resource
Computer Vision for the Humanities: An Introduction to Deep Learning for Image Classification (Part 1)
Resource type
External Resource
Authors, editors and contributors
Daniel van Strien, Kaspar Beelen, Melvin Wevers, Thomas Smits, Katherine McDonough, Nabeel Siddiqui, Alex Wermer-Colan, Michael Black, Catherine DeRose
Topics (keywords)
DH, Open Education, Open Access, Python, Machine learning
Learning outcomes
After completing this lesson, you will have learned:
Abstract
This is the first of a two-part lesson introducing deep learning based computer vision methods for humanities research. Using a dataset of historical newspaper advertisements and the fastai Python library, the lesson walks through the pipeline of training a computer vision model to perform image classification.