FreeComputerBooks.com
Free Computer, Mathematics, Technical Books and Lecture Notes, etc.



Graph Algorithms: Practical Examples in Apache Spark and Neo4j
This book is a practical guide to getting started with graph algorithms for developers and data scientists who have experience using Apache Spark or Neo4j. You'll walk through handson examples that show you how to use graph algorithms in Apache Spark/Neo4j.

Graph Theory  Advanced Algorithms and Applications
Not only will the methods and explanations help you to understand more about graph theory, but you will find it joyful to discover ways that you can apply graph theory in your applications or scientific research.

Probability on Trees and Networks (Russell Lyons, et al)
This book is concerned with certain aspects of discrete probability on infinite graphs that are currently in vigorous development. Of course, finite graphs are analyzed as well, but usually with the aim of understanding infinite graphs and networks.

Graph Theory and Complex Networks (Maarten van Steen)
This book aims to explain the basics of graph theory that are needed at an introductory level for students in computer or information sciences. It also aims to provide an introduction to the modern field of network science.

Graph Theory (Reinhard Diestel)
This book covers the core material of the subject with concise yet reliably complete proofs, while offering glimpses of more advanced methods in each field by one or two deeper results, again with proofs given in full detail.

An Introduction to Combinatorics and Graph Theory
This book walks the reader through the classic parts of Combinatorics and graph theory, while also discussing some recent progress in the area: on the one hand, providing material that will help students learn the basic techniques.

Graph Databases: New Opportunities for Connected Data
This book provides a practical foundation for those who want to apply Graph Database to realworld business solutions. You'll learn why graph database are useful, where they're applicable, and how to design and implement solutions that use them.

Algorithmic Graph Theory (David Joyner, et al)
This is an introductory book on algorithmic graph theory. Theory and algorithms are illustrated using the Sage open source mathematics software. It's especially suitable for computer scientists and mathematicians interested in computational complexity.

Advances in Graph Algorithms (Ton Kloks, YueLi Wang)
This is a book about some currently popular topics such as exponential algorithms, fixedparameter algorithms and algorithms using decomposition trees of graphs which is one of focuses of the book  occupied a whole chapter.

Graph Theory with Applications (J.A. Bondy and U.S.R. Murty)
The primary aim of this book is to present a coherent introduction to graph theory, suitable as a textbook for advanced undergraduate and beginning graduate students in mathematics and computer science.

Graph Theory Lessons (Christopher P. Mawata)
This text covers the important elementary topics of graph theory and its applications. In addition, he presents a large variety of proofs designed to strengthen mathematical techniques and offers challenging opportunities to have fun with mathematics.

Introduction to Graph Theory: Definitions, Traversal, Analysis, etc.
Requiring only high school algebra as mathematical background, the book leads the reader from simple graphs through planar graphs, Euler's formula, Platonic graphs, coloring, the genus of a graph, Euler walks, Hamilton walks, and a discussion of The Seven Bridges of Konigsberg.

New Frontiers in Graph Theory (Yagang Zhang)
The purpose of this book is not only to present the latest state and development tendencies of graph theory, but to bring the reader far enough along the way to enable him to embark on the research problems of his own.

Fractional Graph Theory: A Rational Approach (E. Scheinerman)
In this book the authors explore generalizations of core graph theory notions by allowing real values to substitute where normally only integers would be permitted. The aim is to prove "fractional analogues" of the theorems of traditional graph theory.

Digraphs: Theory, Algorithms and Applications (J. BangJensen)
This book is an essential, comprehensive reference of Digraphs for students, and researchers in mathematics, operations research and computer science.

Algorithms and Data Structures: Apps to Graphics and Geometry
An introductory coverage of algorithms and data structures with application to graphics and geometry. Sample exercises, many with solutions, are included throughout the book.

Lists, Decisions and Graphs  With an Introduction to Probability
In this book, four basic areas of discrete mathematics are presented: Counting and Listing (Unit CL), Functions (Unit Fn), Decision Trees and Recursion (Unit DT), and Basic Concepts in Graph Theory (Unit GT).

Introductory Map Theory (Yanpei Liu)
As an introductory book, this book contains the elementary materials in map theory, including embeddings of a graph, abstract maps, duality, orientable and nonorientable maps, isomorphisms of maps and the enumeration of rooted or unrooted maps, etc.

Graph and Network Theory in Physics: A Short Introduction
This book consists of some of the main areas of research in graph and network theory applied to physics.

Functional Programming and Parallel Graph Rewriting
This is an introduction to the techniques of functional programming, focusing on an alternative computational model  Graph Rewriting Systems.

Architecture for Combinator Graph Reduction (Philip J. Koopman)
The results of cachesimulation experiments with an abstract machine for reducing combinator graphs are presented.

Basic Category Theory (Tom Leinster)
Assuming little mathematical background, this short introduction to Category Theory is ideal for beginning graduate students or advanced undergraduates learning category theory for the first time.

Category Theory for the Sciences (David I. Spivak)
Using databases as an entry to Category Theory, this book explains category theory by examples, and shows that category theory can be useful outside of mathematics as a rigorous, flexible, and coherent modeling language throughout the sciences.




















