Title: Foundations of Data Science
Author: John E. Hopcroft and Ravindran Kannan
Early drafts of the book have been used for both undergraduate and graduate courses.
Background material needed for an undergraduate course has been put in the appendix.
For this reason, the appendix has homework problems.
This book starts with the treatment of high dimensional geometry. Modern data in diverse fields such as Information Processing, Search, Machine Learning, etc., is often represented advantageously as vectors with a large number of components. This is so even in cases when the vector representation is not the natural first choice.