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Can I read Graph Machine Learning: Learn about the latest advancements in graph data to build robust machine learning models on EtoBox?
Graph Machine Learning: Learn about the latest advancements in graph data to build robust machine learning models by Aldo Marzullo, Enrico Deusebio, Claudio Stamile is a nonfiction available to read on EtoBox.
What is Graph Machine Learning: Learn about the latest advancements in graph data to build robust machine learning models about?
Overview Explore the updated edition with new chapters on LLMs, Temporal Graphs, and updated Pytorch Geometric examples to enhance your data science skills. Key Features Master new graph ML techniques with updated Pytorch Geometric examples Explore case studies that demonstrate real-world applications of GML Leverage graphs for advanced tasks in LLMs and Temporal learning Book Description Graph Machine Learning, Second Edition not only revises but expands on its successful first edition, providing you with the latest tools and techniques in graph machine learning. This edition introduces comprehensive updates across all chapters, new chapters on trending topics like LLMs and Temporal Graph Learning, and real-world case studies that illustrate the practical applications of these concepts. From basic graph theory to advanced machine learning models, the book guides you through understanding how data can be represented as graphs to uncover complex patterns and relationships hidden in your data. This edition emphasizes practical application with updated code examples using Pytorch Geometric, making it easier for you to implement what you learn. The expanded content includes detailed ch
Who reads Graph Machine Learning: Learn about the latest advancements in graph data to build robust machine learning models?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Aldo Marzullo, Enrico Deusebio, Claudio Stamile
- Publisher
- Packt Publishing Limited
- Published
- 2025
- Language
- EN
- ISBN
- 9781803248066
- Category
- nonfiction
- Subjects
- Computer Science, Artificial Intelligence (Ai), Stem
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