This book addresses growing demand in the visual humanities for foundational knowledge in data analysis, image processing, and Artificial Intelligence (AI). Intended for readers without prior technical knowledge, its eighteen chapters introduce key concepts in Data Science through examples from art history, visual computing, and cloud technologies. For advanced readers, it explores how digital methods enhance our understanding of our cultural past. Focusing on image-based humanities research, the book demonstrates practical applications using open source software such as R, RStudio, and ImageMagick, along with open data sets from institutions like the MoMA, the Met, and the Rijksmuseum. To effectively analyze data, the choice of means is crucial. In this book, we are using the programming language R as a strategic choice, since it offers distinct advantages over alternative means. R, being an open-source language, accommodates a wide spectrum of data analysis tasks.

Cultural Data Science: An Introduction to R PDF

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