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Graph-Powered Machine Learning /
Graph-Powered Machine Learning teaches you how to exploit the natural relationships in structured and unstructured datasets using graph-oriented machine learning algorithms and tools. In this authoritative book, you'll master the architectures and design practices of graphs, and avoid common pi...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Shelter Island :
Manning Publications,
[2021]
|
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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|---|---|---|---|
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| 003 | OCoLC | ||
| 005 | 20231017213018.0 | ||
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| 008 | 140921s2021 nyu ob 001 0 eng d | ||
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| 100 | 1 | |a Negro, Alessandro, |e author. | |
| 245 | 1 | 0 | |a Graph-Powered Machine Learning / |c Negro, Alessandro. |
| 264 | 1 | |a Shelter Island : |b Manning Publications, |c [2021] | |
| 300 | |a 1 online resource (496 pages) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a text file | ||
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a 1. Machine learning and graphs : an introduction -- 2. Graph data engineering -- 3. Graphs in machine learning applications -- 4. Content-based recommendations -- 5. Collaborative filtering -- 6. Session-based recommendations -- 7. Context-aware and hybrid recommendations -- 8. Basic approaches to graph-powered fraud detection -- 9. Proximity-based algorithms -- 10. Social metwork analysis against fraud -- 11. Graph-based natural language processing -- 12. Knowledge graphs. | |
| 520 | |a Graph-Powered Machine Learning teaches you how to exploit the natural relationships in structured and unstructured datasets using graph-oriented machine learning algorithms and tools. In this authoritative book, you'll master the architectures and design practices of graphs, and avoid common pitfalls. Author Alessandro Negro explores examples from real-world applications that connect GraphML concepts to real world tasks. | ||
| 542 | |f © 2021 Manning Publications Co. All rights reserved. |g 2021 | ||
| 550 | |a Made available through: Safari, an O'Reilly Media Company. | ||
| 588 | |a Online resource; Title from title page (viewed September 13, 2021) | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Machine learning. | |
| 650 | 0 | |a Machine learning |x Graphic methods. | |
| 650 | 0 | |a Graph theory. | |
| 650 | 6 | |a Apprentissage automatique. | |
| 650 | 6 | |a Apprentissage automatique |x Méthodes graphiques. | |
| 650 | 7 | |a Graph theory |2 fast | |
| 650 | 7 | |a Machine learning |2 fast | |
| 650 | 7 | |a Machine learning |x Graphic methods |2 fast | |
| 710 | 2 | |a Safari, an O'Reilly Media Company. | |
| 776 | 0 | 8 | |i Print version: |a Negro, Alessandro. |t Graph-powered machine learning. |d Shelter Island : Manning Publications, [2021] |z 9781617295645 |w (OCoLC)1272889500 |
| 856 | 4 | 0 | |u https://learning.oreilly.com/library/view/~/9781617295645/?ar |z Texto completo (Requiere registro previo con correo institucional) |
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| 994 | |a 92 |b IZTAP | ||