Episode 19: Stylometry with Principal Component Analysis (PCA)

In this episode I show how to conduct principal component analysis and visualize the result using Python. This is a replacement for the original video, with a new title card (original here: https://youtu.be/PdcvVroezQM) ------------- In this tutorial series I will be covering all of the code I teach in my intro to digital humanities class at Leiden University. You can find all of the code at https://www.github.com/vierth/humanit... and the class syllabus at https://www.pvierth.com/s/HackingFall... This is designed to help anyone who has never coded learn the basics of Python for text mining and data visualization. We will be using the Anaconda distribution of Python 3, which you can download here: https://www.anaconda.com/download/ Thanks to Leiden University's ECOLe and Thomas Vorisek for all of the video, audio, and editing work! Thanks also to Robin Fleming of Boston College (who suggested the name "Hacking the Humanities") and Austin Mason of Carleton College (for coming up with the name in the first place).