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Introduction
Reading
Information Visualization in the Humanities
Work Cited
Implementing and Analyzing N-Grams in Python
Advanced Text Analysis In R
Text Analysis with K-Means Clustering
Text Analysis with Term Frequency-Inverse Document Frequency
Topic Modeling and Basic Topic Modeling In R
Text Clustering Based on Tf-Idf Features
Social Network Simulation
Introduction to Principal Component Analysis
Introduction to T-Sne for High Dimensional Visualization
Artificial Neural Networks
Analysis of Artificial Neural Networks
Importance of Texture
Immersion and Interactivity and Museum Exhibits
Accessibility and Universal Design
Appendix
Beumer, L. (2020). Evaluation of Text Document Clustering using k-Means.
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Digital Humanities Tools and Techniques II Copyright © 2022 by Mark Wachowiak, Ph.D. is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License, except where otherwise noted.