Graph Learning – alle Bücher

Hybride KI mit Machine Learning und Knowledge Graphs

Seit den 2010er Jahren hat die Künstliche Intelligenz (KI) durch Erfolge im Machine Learning (ML) einen enormen Schub erfahren. Einerseits durch die stark angewachsene Menge verfügbarer digitaler Daten un…

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Lei Zhu, Zheng Zhang, Jingjing Li
Dynamic Graph Learning for Dimension Reduction and Data Clustering

This book illustrates how to achieve effective dimension reduction and data clustering. The authors explain how to accomplish this by utilizing the advanced dynamic graph learning technique in the era of …

lieferbar innerhalb 2-3 Wochen

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Mayo Oshin, Nuno Campos
Learning LangChain

>Authors Mayo Oshin and Nuno Campos demystify the use of LangChain through practical insights and in-depth tutorials. Starting with basic concepts, this book shows you step-by-step how to build a produ…

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Suprakas Sinha Ray, Jonathan Tersur Orasugh, Lesego Tabea Temane
Graphene-Bearing Polymer Composites

This book explores recent developments in electrically conducting graphene-containing polymer composites for electromagnetic interference (EMI) shielding and flame-retardant applications. It emphasizes th…

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Keita Broadwater, Namid Stillman
Graph Neural Networks in Action

About the bookIn Graph Neural Networks in Action you will create deep learning models that are perfect for working with interconnected graph data. Start with a comprehensive introduction to graph data's u…

lieferbar ab 2.7.2025.

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Alessandro Negro, Vlastimil Kus, Giuseppe Futia, Fabio Montagna
Knowledge Graphs and Llms in Action

Knowledge graphs help understand relationships between the objects, events, situations, and concepts in your data so you can readily identify important patterns and make better decisions. This book provid…

lieferbar ab 26.8.2025.

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Weili Guan, Liqiang Nie, Dongliang Zhou, Xuemeng Song
Advanced Multimodal Compatibility Modeling and Recommendation

This Second Edition sheds light on state-of-the-art theories and practices in multimodal compatibility modeling and recommendation, offering comprehensive insights into this evolving field. This topic, an…

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Machine Learning for Causal Inference

This book provides a deep understanding of the relationship between machine learning and causal inference. It covers a broad range of topics, starting with the preliminary foundations of causal inference,…

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Elliptically Symmetric Distributions in Signal Processing and Machine Learning

This book constitutes a review of recent developments in the theory and practical exploitation of the elliptical model for measured data in both classical and emerging areas of signal processing. It devel…

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Discovery Science

The two-volume set LNAI 15243 + 15244 constitutes the proceedings of the 27th International Conference on Discovery Science, DS 2024, which took place in Pisa, Italy, during October 14-16, 2024.The 53 ful…

lieferbar innerhalb 2-3 Wochen

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Discovery Science

The two-volume set LNAI 15243 + 15244 constitutes the proceedings of the 27th International Conference on Discovery Science, DS 2024, which took place in Pisa, Italy, during October 14-16, 2024.The 53 ful…

lieferbar innerhalb 2-3 Wochen

Buch

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