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Can I read Graph Machine Learning : Take Graph Data to the Next Level by Applying Machine Learning Techniques and Algorithms on EtoBox?
Graph Machine Learning : Take Graph Data to the Next Level by Applying Machine Learning Techniques and Algorithms by Claudio Stamile, Aldo Marzullo, Enrico Deusebio is a science book available to read on EtoBox.
What is Graph Machine Learning : Take Graph Data to the Next Level by Applying Machine Learning Techniques and Algorithms about?
Build machine learning algorithms using graph data and efficiently exploit topological information within your models Key Features Implement machine learning techniques and algorithms in graph data Identify the relationship between nodes in order to make better business decisions Apply graph-based machine learning methods to solve real-life problems Book Description Graph Machine Learning provides a new set of tools for processing network data and leveraging the power of the relation between entities that can be used for predictive, modeling, and analytics tasks. You will start with a brief introduction to graph theory and graph machine learning, understanding their potential. As you proceed, you will become well versed with the main machine learning models for graph representation learning: their purpose, how they work, and how they can be implemented in a wide range of supervised and unsupervised learning applications. You'll then build a complete machine learning pipeline, including data processing, model training, and prediction in order to exploit the full potential of graph data. Moving ahead, you will cover real-world scenarios such as extracting data from social netw
Who reads Graph Machine Learning : Take Graph Data to the Next Level by Applying Machine Learning Techniques and Algorithms?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Claudio Stamile, Aldo Marzullo, Enrico Deusebio
- Publisher
- Packt Publishing, Limited; Packt Publishing
- Published
- 2021
- Language
- EN
- ISBN
- 9781800204492
- Category
- science
- Subjects
- Science, Computer Science, Stem
- Rating
- 4.1 / 5 (72 ratings)
- Updated
- 2026-03-14
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