Graph Machine Learning - Second Edition : Learn about the latest advancements in graph data to build robust machine learning models

Lingua: inglese

Editore: Packt Publishing Jul 2025, 2025

1803248068 / 9781803248066

Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

Venditore con 5 stelle

Venditore AbeBooks dal 14 agosto 2006

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Condizione: Nuovo

EUR 89,48

EUR 35,00 spedizione 
Spedito da Germania a U.S.A.

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Descrizione dell’articolo da parte del venditore

Neuware - Enhance your data science skills with this updated edition featuring new chapters on LLMs, temporal graphs, and updated examples with modern frameworks, including PyTorch Geometric and DGLFree with your book: DRM-free PDF version + access to Packt's next-gen Reader\*Key Features:- Master new graph ML techniques through updated examples using PyTorch Geometric and Deep Graph Library (DGL)- Explore GML frameworks and their main characteristics- Leverage LLMs for machine learning on graphs and learn about temporal learning- Purchase of the print or Kindle book includes a free PDF Elektronisches BuchBook Description:Graph Machine Learning, Second Edition builds on its predecessor's success, delivering the latest tools and techniques for this rapidly evolving field. From basic graph theory to advanced ML models, you'll learn how to represent data as graphs to uncover hidden patterns and relationships, with practical implementation emphasized through refreshed code examples. This thoroughly updated edition replaces outdated examples with modern alternatives such as PyTorch and DGL, available on GitHub to support enhanced learning.The book also introduces new chapters on large language models and temporal graph learning, along with deeper insights into modern graph ML frameworks. Rather than serving as a step-by-step tutorial, it focuses on equipping you with fundamental problem-solving approaches that remain valuable even as specific technologies evolve. You will have a clear framework for assessing and selecting the right tools.By the end of this book, you'll gain both a solid understanding of graph machine learning theory and the skills to apply it to real-world challenges.\*Email sign-up and proof of purchase requiredWhat You Will Learn:- Implement graph ML algorithms with examples in StellarGraph, PyTorch Geometric, and DGL- Apply graph analysis to dynamic datasets using temporal graph ML- Enhance NLP and text analytics with graph-based techniques- Solve complex real-world problems with graph machine learning- Build and scale graph-powered ML applications effectively- Deploy and scale your application seamlesslyWho this book is for:This book is for data scientists, ML professionals, and graph specialists looking to deepen their knowledge of graph data analysis or expand their machine learning toolkit. Prior knowledge of Python and basic machine learning principles is recommended.Table of Contents- Getting Started with Graphs- Graph Machine Learning- Neural Networks and Graphs- Unsupervised Graph Learning- Supervised Graph Learning- Solving Common Graph-Based Machine Learning Problems- Social Network Graphs- Text Analytics and Natural Language Processing Using Graphs- Graph Analysis for Credit Card Transactions- Building a Data-Driven Graph-Powered Application- Temporal Graph Machine Learning- GraphML and LLMs- Novel Trends on Graphs.…

Codice articolo 9781803248066

Titolo
Graph Machine Learning - Second Edition : Learn about the latest advancements in graph data to build robust machine learning models
Autore
Aldo Marzullo
Editore
Packt Publishing Jul 2025
Anno di pubblicazione
2025
Condizione
Neu
Rilegatura
Taschenbuch
Lingua
inglese
ISBN 10
1803248068
ISBN 13
9781803248066
Edizione
seconda edizione
Peso dell'articolo
805 grammi
Dimensioni
235x191x24 mm

AHA-BUCH GmbH

Einbeck, Germania

Venditore con 5 stelle

Venditore AbeBooks dal 14 agosto 2006

Tariffe di spedizione da Germania a U.S.A.

ArticoloDa 7 a 10 giorni lavorativiDa 5 a 7 giorni lavorativi
Primo articoloEUR 35,00EUR 45,00
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