Title Statements
- Full title :Deep learning on graphs / Yao Ma, Jiliang Tang.
Summary
Deep learning on graphs has become one of the hottest topics in machine learning. The book consists of four parts to best accommodate our readers with diverse backgrounds and purposes of reading. Part 1 introduces basic concepts of graphs and deep learning; Part 2 discusses the most established methods from the basic to advanced settings; Part 3 presents the most typical applications including natural language processing, computer vision, data mining, biochemistry and healthcare; and Part 4 describes advances of methods and applications that tend to be important and promising for future research. The book is self-contained, making it accessible to a broader range of readers including (1) senior undergraduate and graduate students; (2) practitioners and project managers who want to adopt graph neural networks into their products and platforms; and (3) researchers without a computer science background who want to use graph neural networks to advance their disciplines.
Read More ↓Edition Statements
- Publication Date:©2021
Publication Statements
- Publisher(s):Cambridge University Press
- Place of Publication:Cambridge, United Kingdom
- Language:eng
- Publication Date:©2021
The Physical Object
- Description:1 online resource (xviii, 320 pages) : : illustrations
Edition Identifiers
- ISBN:9781108924184, 1108924182
- oclc:on1267537609
- LC Classification:Q325.5
- Dewey Decimal:006.3/1
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Deep Learning on Graphs -- (.pdf)
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