Recommended Literature for Data Science Students (Postgraduate)

Last update: 2024-07-08. This list is a work in progress.

Applied Statistics

Arnold, B.C. (2015). Pareto Distributions. CRC Press.

Random Graphs / Complex Networks

Networks, Crowds, and Markets: Reasoning About a Highly Connected World by David Easley and Jon Kleinberg https://www.cs.cornell.edu/home/kleinber/networks-book/

Information, Physics, and Computation by Marc Mézard and Andrea Montanari https://web.stanford.edu/~montanar/RESEARCH/book.html

Random Graphs and Complex Networks by Remco van der Hofstad https://www.win.tue.nl/~rhofstad/NotesRGCN.html

Dynamics on Graphs by Rick Durrett https://services.math.duke.edu/~rtd/DoG/DoG.html

Networks by MEJ Newman

Natural Language Processing

Jurafsky D and Martin JH, Speech and Language Processing (3rd ed. draft), https://web.stanford.edu/~jurafsky/slpdraft/

Eisenstein J, Natural Language Processing, https://github.com/jacobeisenstein/gt-nlp-class/tree/master/notes

Goldberg Y, A Primer on Neural Network Models for Natural Language Processing, http://u.cs.biu.ac.il/~yogo/nnlp.pdf