This chapter presents a summary review of prerequisite concepts from statistics, mathematics and computer science, although readers are expected to have a nodding familiarity with most of them. It also provides some background on a number of computational problems and data sets used in the book or particularly useful for data science and dimensionality reduction; as well as a review of computing environments and platforms that could be used as a playground to run and test the methods and solutions described in this book. The aim is to provide a refresher of what they are and point to sources in the literature where they could be studied in more detail, if needed.
Dimensionality Reduction in Data Science
Garzon, M., Deng, L., Kumar, N., Venugopal, D., Jana, K., & Yang, C. (2022). Appendices. Dimensionality Reduction in Data Science, 219-265. https://doi.org/10.1007/978-3-031-05371-9_11