Graph Algorithms 2024 pdf epub mobi 电子书

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Graph Algorithms 2024 pdf epub mobi 电子书著者简介

Mark Needham is a graph advocate and Developer Relations Engineer at Neo4j. Mark helps users embrace graphs and Neo4j, building sophisticated solutions to challenging data problems. Mark has deep expertise in graph data having previously helped to build Neo4j's Causal Clustering system. Mark writes about his experiences of being a graphista on a popular blog at markhneedham.com.

Amy Hodler is a network science devotee and AI and Graph Analytics Program Manager at Neo4j. She promotes the use of graph analytics to reveal structures within real-world networks and predict dynamic behavior. Amy helps teams apply novel approaches to generate new opportunities at companies such as EDS, Microsoft, Hewlett-Packard (HP), Hitachi IoT, and Cray Inc. Amy has a love for science and art with a fascination for complexity studies and graph theory.

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发表于2024-11-21

Graph Algorithms 2024 pdf epub mobi 电子书

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出版者:O'Reilly Media

作者:Mark Needham

出品人:

页数:249

译者:

出版时间:2019-6-4

价格:USD 69.99

装帧:Paperback

isbn号码:9781492047681

丛书系列:

图书标签: 计算机算法图 Algorithms 编程 Neo4j 机器学习 Algorithm

Graph Algorithms 2024 pdf epub mobi 电子书图书描述

Discover how graph algorithms can help you leverage the relationships within your data to develop more intelligent solutions and enhance your machine learning models. You’ll learn how graph analytics are uniquely suited to unfold complex structures and reveal difficult-to-find patterns lurking in your data. Whether you are trying to build dynamic network models or forecast real-world behavior, this book illustrates how graph algorithms deliver value—from finding vulnerabilities and bottlenecks to detecting communities and improving machine learning predictions.

This practical book walks you through hands-on examples of how to use graph algorithms in Apache Spark and Neo4j—two of the most common choices for graph analytics. Also included: sample code and tips for over 20 practical graph algorithms that cover optimal pathfinding, importance through centrality, and community detection.

Learn how graph analytics vary from conventional statistical analysis

Understand how classic graph algorithms work, and how they are applied

Get guidance on which algorithms to use for different types of questions

Explore algorithm examples with working code and sample datasets from Spark and Neo4j

See how connected feature extraction can increase machine learning accuracy and precision

Walk through creating an ML workflow for link prediction combining Neo4j and Spark

Graph Algorithms 2024 pdf epub mobi 电子书

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现在最火的是什么？是基于图的机器学习。如果你只想学这方面的内容，那么恭喜了，你可以省下读这本书的时间去找其它资料。起码我在一开始是抱着如此想法翻阅这本书的，虽然其中有一章是介绍图算法与机器学习，但其粗浅程度太甚。作者是挺诚实的，书名中就说了这是本实践工具书，想好好学算法就去读其它书，但就实践指南的功能而言，这书中Spark与Neo4j代码在我看来实在是欠缺良好的注释说明，还好几乎没有满页满页的无注释代码，不然可以直接给最差评。作者没有给出完备的注释，也许是觉得几段文字说明已经足够，但我还是那句话，有相应能力的读者没必要读你这本书，没有相应能力的读者无法真正效率满满的读你这本书。此书介绍图相关基本算法的代码实现，路径探索、节点定位、子图分类以及挖掘各种图属性的具体代码，如果不求甚解还是可读的。

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