Data Science
We are pleased to announce the release of the first edition of “Exploring Data Science with R and the Tidyverse: A Concise Introduction” by Jerry Bonnell and Mitsunori Ogihara, now available online (eBook) or in print (hardback or paperback) through Taylor Francis/Routledge. Read more “New Book: Exploring Data Science with R and the Tidyverse”
Publications
Data science is one of the fastest-growing fields because of its ability to address analytic needs. However, the supply of data scientists has remained limited. Academic institutions must adapt to meet demand through programs to train future data scientists. Read more “IEEE Computer Journal: Challenges and Issues in Data Science Education”
Courses
The volume of data collected today is growing astronomically as our computers, phones, and smart devices track our every move, purchase, and desire. Yet, the number of people who can sift through this data to find useful information remains a meager percentage of the workforce. Read more ““Data Science for the World” Inspires Future Data Scientists”
Publications
Morphological adornment of text in Text Encoding Initiative (TEI) XML can be useful for studies in textual analysis. MorphAdorner is a principal tool for providing such functionality in English texts. However, its practical use is limited when the input XML contains branching text, e.g. Read more “Hoshi: A Japanese Morphological Adorner for TEI XML”