Graph Algorithms for Data Science (Paperback)

Tomaz Bratanic

6 évaluations par Goodreads

Langue : anglais

Edité par Manning Publications, New York, 2024

1617299464 / 9781617299469

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Paperback. Graphs are the natural way to understand connected data. This book explores the most important algorithms and techniques for graphs in data science, with practical examples and concrete advice on implementation and deployment. In Graph Algorithms for Data Science you will learn: Labeled-property graph modelingConstructing a graph from structured data such as CSV or SQLNLP techniques to construct a graph from unstructured dataCypher query language syntax to manipulate data and extract insightsSocial network analysis algorithms like PageRank and community detectionHow to translate graph structure to a ML model input with node embedding modelsUsing graph features in node classification and link prediction workflows Graph Algorithms for Data Science is a hands-on guide to working with graph-based data in applications like machine learning, fraud detection, and business data analysis. It's filled with fascinating and fun projects, demonstrating the ins-and-outs of graphs. You'll gain practical skills by analyzing Twitter, building graphs with NLP techniques, and much more. You don't need any graph experience to start benefiting from this insightful guide. These powerful graph algorithms are explained in clear, jargon-free text and illustrations that makes them easy to apply to your own projects. about the technology Graphs reveal the relationships in your data. Tracking these interlinking connections reveals new insights and influences and lets you analyze each data point as part of a larger whole. This interconnected data is perfect for machine learning, as well as analyzing social networks, communities, and even product recommendations. about the book Graph Algorithms for Data Science teaches you how to construct graphs from both structured and unstructured data. You'll learn how the flexible Cypher query language can be used to easily manipulate graph structures, and extract amazing insights. The book explores common and useful graph algorithms like PageRank and community detection/clustering algorithms. Each new algorithm you learn is instantly put into action to complete a hands-on data project, including modeling a social network! Finally, you'll learn how to utilize graphs to upgrade your machine learning, including utilizing node embedding models and graph neural networks. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

N° de réf. du vendeur 9781617299469

Titre
Graph Algorithms for Data Science (Paperback)
Auteur
Tomaz Bratanic
Éditeur
Manning Publications, New York
Année de publication
2024
État de l'article
new
Reliure
Paperback
Langue
anglais
ISBN à 10 chiffres
1617299464
ISBN à 13 chiffres
9781617299469

Grand Eagle Retail

Bensenville, IL, Etats-Unis

Vendeur avec une évaluation de 5 étoiles

Vendeur AbeBooks depuis 12 octobre 2005

Frais d'expédition à l'intérieur de ce pays : Etats-Unis

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