Modern Graph Theory Algorithms With Python

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Modern Graph Theory Algorithms With Python

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Author : Colleen M. Farrelly
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-06-07

Modern Graph Theory Algorithms With Python written by Colleen M. Farrelly and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-07 with Computers categories.

Solve challenging and computationally intensive analytics problems by leveraging network science and graph algorithms Key Features Learn how to wrangle different types of datasets and analytics problems into networks Leverage graph theoretic algorithms to analyze data efficiently Apply the skills you gain to solve a variety of problems through case studies in Python Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionWe are living in the age of big data, and scalable solutions are a necessity. Network science leverages the power of graph theory and flexible data structures to analyze big data at scale. This book guides you through the basics of network science, showing you how to wrangle different types of data (such as spatial and time series data) into network structures. You’ll be introduced to core tools from network science to analyze real-world case studies in Python. As you progress, you’ll find out how to predict fake news spread, track pricing patterns in local markets, forecast stock market crashes, and stop an epidemic spread. Later, you’ll learn about advanced techniques in network science, such as creating and querying graph databases, classifying datasets with graph neural networks (GNNs), and mining educational pathways for insights into student success. Case studies in the book will provide you with end-to-end examples of implementing what you learn in each chapter. By the end of this book, you’ll be well-equipped to wrangle your own datasets into network science problems and scale solutions with Python.What you will learn Transform different data types, such as spatial data, into network formats Explore common network science tools in Python Discover how geometry impacts spreading processes on networks Implement machine learning algorithms on network data features Build and query graph databases Explore new frontiers in network science such as quantum algorithms Who this book is for If you’re a researcher or industry professional analyzing data and are curious about network science approaches to data, this book is for you. To get the most out of the book, basic knowledge of Python, including pandas and NumPy, as well as some experience working with datasets is required. This book is also ideal for anyone interested in network science and learning how graph algorithms are used to solve science and engineering problems. R programmers may also find this book helpful as many algorithms also have R implementations.

Graph Machine Learning

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Author : Aldo Marzullo
language : en
Publisher: Packt Publishing Ltd
Release Date : 2025-07-18

Graph Machine Learning written by Aldo Marzullo and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-18 with Mathematics categories.

Enhance your data science skills with this updated edition featuring new chapters on LLMs, temporal graphs, and updated examples with modern frameworks, including PyTorch Geometric and DGL Free with your book: DRM-free PDF version + access to Packt's next-gen Reader* Key Features Master new graph ML techniques through updated examples using PyTorch Geometric and Deep Graph Library (DGL) Explore GML frameworks and their main characteristics Leverage LLMs for machine learning on graphs and learn about temporal learning Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionGraph Machine Learning, Second Edition builds on its predecessor’s success, delivering the latest tools and techniques for this rapidly evolving field. From basic graph theory to advanced ML models, you’ll learn how to represent data as graphs to uncover hidden patterns and relationships, with practical implementation emphasized through refreshed code examples. This thoroughly updated edition replaces outdated examples with modern alternatives such as PyTorch and DGL, available on GitHub to support enhanced learning. The book also introduces new chapters on large language models and temporal graph learning, along with deeper insights into modern graph ML frameworks. Rather than serving as a step-by-step tutorial, it focuses on equipping you with fundamental problem-solving approaches that remain valuable even as specific technologies evolve. You will have a clear framework for assessing and selecting the right tools. By the end of this book, you’ll gain both a solid understanding of graph machine learning theory and the skills to apply it to real-world challenges. *Email sign-up and proof of purchase required -What you will learn Implement graph ML algorithms with examples in StellarGraph, PyTorch Geometric, and DGL Apply graph analysis to dynamic datasets using temporal graph ML Enhance NLP and text analytics with graph-based techniques Solve complex real-world problems with graph machine learning Build and scale graph-powered ML applications effectively Deploy and scale your application seamlessly Who this book is for This book is for data scientists, ML professionals, and graph specialists looking to deepen their knowledge of graph data analysis or expand their machine learning toolkit. Prior knowledge of Python and basic machine learning principles is recommended.

An Introduction To Computational Systems Biology

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Author : Karthik Raman
language : en
Publisher: CRC Press
Release Date : 2021-05-30

An Introduction To Computational Systems Biology written by Karthik Raman and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-30 with Computers categories.

This book delivers a comprehensive and insightful account of applying mathematical modelling approaches to very large biological systems and networks—a fundamental aspect of computational systems biology. The book covers key modelling paradigms in detail, while at the same time retaining a simplicity that will appeal to those from less quantitative fields. Key Features: A hands-on approach to modelling Covers a broad spectrum of modelling, from static networks to dynamic models and constraint-based models Thoughtful exercises to test and enable understanding of concepts State-of-the-art chapters on exciting new developments, like community modelling and biological circuit design Emphasis on coding and software tools for systems biology Companion website featuring lecture videos, figure slides, codes, supplementary exercises, further reading, and appendices: https://ramanlab.github.io/SysBioBook/ An Introduction to Computational Systems Biology: Systems-Level Modelling of Cellular Networks is highly multi-disciplinary and will appeal to biologists, engineers, computer scientists, mathematicians and others.

Computational Science And Computational Intelligence

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Author : Hamid R. Arabnia
language : en
Publisher: Springer Nature
Release Date : 2025-08-09

Computational Science And Computational Intelligence written by Hamid R. Arabnia and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-09 with Computers categories.

The CCIS book constitutes selected papers accepted in the Research Track on Education of the 11th International Conference on Computational Science and Computational Intelligence, CSCI 2024, which took place in Las Vegas, NV, USA, during December 11–13, 2024. The 26 full papers included in this book were carefully reviewed and selected from a total of 155 submissions. They were organized in topical sections on subject-specific education and curriculum design; education and artificial intelligence; teaching and learning strategies and related reserach studies.

Concepts Applications And Simulations In Combinatorics

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Author : Drivet, Alessio
language : en
Publisher: IGI Global
Release Date : 2025-09-05

Concepts Applications And Simulations In Combinatorics written by Drivet, Alessio and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-05 with Mathematics categories.

Combinatorics, the mathematical study of counting and combinations, plays a foundational role across various scientific and technological disciplines. To understand complex networks and algorithms, combinatorics helps with cryptography and statistical physics. As the field evolves, using advanced applications and computer base simulations become integral using combinatorial structures and hypothesis. By blending abstract theory with practical computation, modern combinatorics continues to drive innovation and discovery across mathematics and beyond. Concepts, Applications, and Simulations in Combinatorics offers a comprehensive yet accessible exploration of combinatorics, emphasizing its relevance across different educational levels. It examines the philosophical and practical significance of discrete mathematics, highlighting how combinatorics supports critical thinking and problem-solving in diverse fields. Covering topics such as combinatorial calculus, graph counting, and probability, this book is an excellent resource for mathematicians, researchers, academicians, educators, and more.

Cornell University Courses Of Study

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Author : Cornell University
language : en
Publisher:
Release Date : 2007

Cornell University Courses Of Study written by Cornell University and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Universities and colleges categories.

Algebraic Graph Algorithms

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Author : K. Erciyes
language : en
Publisher: Springer Nature
Release Date : 2021-11-17

Algebraic Graph Algorithms written by K. Erciyes and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-17 with Computers categories.

This textbook discusses the design and implementation of basic algebraic graph algorithms, and algebraic graph algorithms for complex networks, employing matroids whenever possible. The text describes the design of a simple parallel matrix algorithm kernel that can be used for parallel processing of algebraic graph algorithms. Example code is presented in pseudocode, together with case studies in Python and MPI. The text assumes readers have a background in graph theory and/or graph algorithms.

College Of Engineering University Of Michigan Publications

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Author : University of Michigan. College of Engineering
language : en
Publisher:
Release Date : 2008

College Of Engineering University Of Michigan Publications written by University of Michigan. College of Engineering and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Catalogs, College categories.

Also contains brochures, directories, manuals, and programs from various College of Engineering student organizations such as the Society of Women Engineers and Tau Beta Pi.

Stanford Bulletin

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Author :
language : en
Publisher:
Release Date : 2006

Stanford Bulletin written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with categories.

The Cumulative Book Index

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Author :
language : en
Publisher:
Release Date : 1995

The Cumulative Book Index written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with American literature categories.

A world list of books in the English language.