Graph Algorithms by Mark Needham and Amy E. Hodler Copyright © 2019 Amy Hodler and Mark Needham. All rights reserved. What’s in This Book 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. Although our algorithm examples utilize the Spark and Neo4j platforms, this book will also be helpful for understanding more general graph concepts, regardless of your choice of graph technologies. The first two chapters provide an introduction to graph analytics, algorithms, and theory. The third chapter briefly covers the platforms used in this book before we dive into three chapters focusing on classic graph algorithms: pathfinding, centrality, and community detection. We wrap up the book with two chapters showing how graph algorithms are used within workflows: one for general analysis and one for machine learning. At the beginning of each category of algorithms, there is a reference table to help you quickly jump to the relevant algorithm. For each algorithm, you’ll find: • An explanation of what the algorithm does • Use cases for the algorithm and references to where you can learn more • Example code providing concrete ways to use the algorithm in Spark, Neo4j, or both 图方法方面最新的参考书,本文理论实践兼备(看标题就知道了),内容高清无码书签完整诚不我欺,强烈推荐给需要的朋友!
2019-12-21 20:24:10 10.86MB Graph Algorithm Apache Spark
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2019-12-21 20:12:50 6.27MB tensorflow
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802.11官方协议,定义了MAC层和PHY层,有助于对协议的学习和掌握.pdf
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