Modern Graph Theory Algorithms with Python: Harness the power of graph algorithms and real-world network applications using Python

by Colleen Farrelly, Franck Kalala Mutombo

290 pages, Paperback

Published June 7, 2024

About the author

Colleen M. Farrelly primarily writes to explore her experiences and remember those who have passed on. Over 62 of her poems and nonfiction articles have been published in over 22 journals, and she has published 5 books, Places and Faces, Portraits of War, Phoenix Rising, The War Folder, and Juvenilia. She donates a portion (30%) of her profits to nonprofits focused on returning Veterans and providing for the homeless.

Colleen was born into a family with several generations of military service and a community that welcomed Bosnian and Hmong refugees when she was young. Her early coursework and internships focused on studying and documenting humanitarian crises with a focus on Bosnia and Sri Lanka, and she was a medical volunteer for several years (including in America’s inner cities and various cities in Sub-Saharan Africa). As an MD/PhD student, she spent several months studying in the Miami-Dade County morgue, learning forensics and documentation of medical evidence. Many of Colleen's poems and novellas (particularly The War Folder) draw from these experiences.

She is currently a data scientist, with previous projects including Ebola spread modeling to help formulate an emergency plan in Mali, developing medical risk monitoring systems for the U.S. Navy, mining failed pharmaceutical trials for subgroups of responders, and setting up analyses to help personalize education. Colleen’s scientific research includes psychometrics, topological data analysis, and ensemble learning. She plans to write a layperson's guide to machine learning and computational mathematics in 2018.

Reviews

[Andrey Lukyanenko · Rating 3 out of 5]

"Modern Graph Theory Algorithms with Python" aims to provide a comprehensive overview of graph theory concepts with practical Python examples. While the book covers an impressive range of topics and provides a substantial amount of information, there are several areas where it could be improved.

What I liked:

Comprehensive Coverage: The book tackles many graph theory concepts, which could be valuable for readers looking to dive deep into the subject. Its ambitious scope makes it a potentially useful reference for those already familiar with the basics of graph algorithms.

Practical Examples: The authors include a range of Python code snippets to illustrate different algorithms. This hands-on approach could be beneficial for readers who prefer learning through coding.

Visual Elements: There are plenty of images and diagrams that attempt to clarify some of the graph theory concepts. These can be helpful for those who find visual aids useful when learning complex topics.

What could be improved:

Overuse of Images: Despite their potential to enhance understanding, many of the images feel somewhat redundant. It sometimes appears that the authors included them merely to add volume to the book, rather than to contribute meaningfully to the explanations.

Introduction of Complex Terminology: The book introduces a plethora of complex terms, sometimes without adequate explanation or context. This approach can overwhelm readers, especially those new to graph theory.

Frequent Switching of Ideas: The text often jumps between different concepts and introduces new ones without sufficient elaboration. This can be confusing and makes it difficult to follow the overall structure of the material.

Overall Impression:

The book has its strengths in terms of breadth and practical coding elements. However, it falls short in its presentation and pacing - for beginners or those looking for a smoother learning experience, this book might be more challenging than helpful.