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Añadir al carritoPaperback / softback. Condición: New. New copy - Usually dispatched within 2 working days. 702.
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Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
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Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de America
EUR 60,07
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Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 59,74
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Librería: California Books, Miami, FL, Estados Unidos de America
EUR 59,60
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Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
Original o primera edición
EUR 65,50
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Añadir al carritoCondición: New. 2024. 1st Edition. paperback. . . . . .
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Publicado por Pearson Education Feb 2024, 2024
ISBN 10: 1617299464 ISBN 13: 9781617299469
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 62,52
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Añadir al carritoTaschenbuch. Condición: Neu. Neuware - 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:
EUR 78,72
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Añadir al carritoCondición: New. 2024. 1st Edition. paperback. . . . . . Books ship from the US and Ireland.
EUR 61,17
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Añadir al carritoCondición: New. Über den AutorToma 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, .
EUR 72,59
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Librería: INDOO, Avenel, NJ, Estados Unidos de America
EUR 45,72
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Añadir al carritoCondición: As New. Unread copy in mint condition.
Librería: INDOO, Avenel, NJ, Estados Unidos de America
EUR 45,77
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Librería: Russell Books, Victoria, BC, Canada
EUR 65,00
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Añadir al carritopaperback. Condición: New. Special order direct from the distributor.
Librería: Goodwill Books, Hillsboro, OR, Estados Unidos de America
EUR 33,99
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Añadir al carritoCondición: Good. Signs of wear and consistent use.
Publicado por Manning Publications, New York, 2024
ISBN 10: 1617299464 ISBN 13: 9781617299469
Idioma: Inglés
Librería: Grand Eagle Retail, Fairfield, OH, Estados Unidos de America
EUR 64,73
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Añadir al carritoPaperback. Condición: new. 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.