June 2024
Intermediate to advanced
290 pages
7h 52m
English
This part of the book builds the practical and theoretical foundations of network science and introduces two Python packages useful in analyzing networks. Part 1 details several examples of data science problems that can be formulated as network science problems, including problems to do with social relationship data, neural network architectures, ontologies, time series data, and spatiotemporal data. This part also establishes foundational topics in graph theory, including categories of graphs and formal definitions, and introduces the igraph and NetworkX Python packages through example networks.
Part 1 has the following chapters:
Read now
Unlock full access