Graph Algorithms for Data Science
(Sprache: Englisch)
Graph Algorithms for Data Science teaches you how to construct graphs from both structured and unstructured data. Youll learn how the flexible Cypher query language can be used to easily manipulate graph structures, and extract amazing insights. Graph...
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Klappentext zu „Graph Algorithms for Data Science “
Graph Algorithms for Data Science teaches you how to construct graphs from both structured and unstructured data. Youll learn how the flexible Cypher query language can be used to easily manipulate graph structures, and extract amazing insights. Graph Algorithms for Data Science is a hands-on guide to working with graph-based data in applications. Its filled with fascinating and fun projects, demonstrating the ins-and-outs of graphs. Youll gain practical skills by analyzing Twitter, building graphs with NLP techniques, and much more. These powerful graph algorithms are explained in clear, jargon-free text and illustrations that makes them easy to apply to your own projects.
Inhaltsverzeichnis zu „Graph Algorithms for Data Science “
table of contents detailed TOCREAD IN LIVEBOOK1GRAPHS AND NETWORK SCIENCE: AN INTRODUCTIONREAD IN LIVEBOOK2REPRESENTING NETWORK STRUCTURE - DESIGN YOUR FIRST GRAPH MODELREAD IN LIVEBOOK3YOUR FIRST STEPS WITH THE CYPHER QUERY LANGUAGEREAD IN LIVEBOOK4CYPHER AGGREGATIONS AND SOCIAL NETWORK ANALYSIS5 INFERRING NETWORKS AND MONOPARTITE PROJECTIONS6 CONSTRUCT A GRAPH USING NLP TECHNIQUES7 NODE EMBEDDINGS AND CLASSIFICATION8 IMPROVE DOCUMENT CLASSIFICATION WITH GRAPH NEURAL NETWORKS9 PREDICT NEW CONNECTIONS10 KNOWLEDGE GRAPH COMPLETIONREAD IN LIVEBOOKAPPENDIX A: ADJACENCY MATRIX
Autoren-Porträt von Tomaz Bratanic
Toma Bratani is a network scientist at heart, working at the intersection of graphs and machine learning. He has applied these graph techniques to projects in various domains including fraud detection, biomedicine, business-oriented analytics, and recommendations.
Bibliographische Angaben
- Autor: Tomaz Bratanic
- 2023, 325 Seiten, Maße: 18,7 x 23,5 cm, Taschenbuch, Englisch
- Verlag: Pearson Studium
- ISBN-10: 1617299464
- ISBN-13: 9781617299469
- Erscheinungsdatum: 26.12.2023
Sprache:
Englisch
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