Network Models for Data Science

 In an evermore technological worlds, the need to understand the connections between various venders, groups and devices has never been so important. 

The study of complex networks, or (as this box refers to them as) network science makes sense of these complicated systems in terms of extended methods applied to graph theory.

The text first begins with an excellent review and introduction to network science, which provides context in terms of various real world examples. Then, it reviews introductory graph theory (which is very much appreciated for those that are non experts in the field), before delving into more succinct aspects of. network models. 

This text is certainly aimed at those more familiar with the mathematician style of communication; ideas are presented through the usual "proof", "theorem" and "lemma". Moreover, the text assume at least an undergraduate level understanding of statistics and mathematics, which means that this text is primarily aimed at graduate to researcher  reader. 

However, this text does provided a full, well thought out contextual introduction to network science, and provides a firm grounding for further exploration into the field.  


Network Models for Data Science 

by Alan Julian Izenman

ISBN: 9781108835763

  • Price: £ 56.99

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