Ranganath sunku (5 Ergebnisse)
- Hardcover
Anbieter: PBShop.store UK, Fairford, GLOS, Vereinigtes KönigreichPBShop.store UK
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 131,72
EUR 7,88 VersandVersand von Vereinigtes Königreich nach USAAnzahl: 15 verfügbar
HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
- Hardcover
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes KönigreichRia Christie Collections
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 139,12
EUR 13,97 VersandVersand von Vereinigtes Königreich nach USAAnzahl: Mehr als 20 verfügbar
Zustand: New. In English.
- Hardcover
Anbieter: moluna, Greven, Deutschlandmoluna
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 143,79
EUR 48,99 VersandVersand von Deutschland nach USAAnzahl: Mehr als 20 verfügbar
Zustand: New.
- Hardcover
Anbieter: Kennys Bookstore, Olney, MD, USAKennys Bookstore
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 223,63
EUR 9,04 VersandVersand innerhalb von USAAnzahl: Mehr als 20 verfügbar
Zustand: New. 2024. 1st Edition. hardcover. . . . . . Books ship from the US and Ireland.
- Hardcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 197,00
EUR 64,77 VersandVersand von Deutschland nach USAAnzahl: 2 verfügbar
Buch. Zustand: Neu. Neuware - Comprehensive overview of the fledgling domain of federated learning (FL), explaining emerging FL methods, architectural approaches, enabling frameworks, and applications Model Optimization Methods for Efficient and Edge AI explores AI model engineering, evaluation, refinement, optimization, and dep…loyment across multiple cloud environments (public, private, edge, and hybrid). It presents key applications of the AI paradigm, including computer vision (CV) and Natural Language Processing (NLP), explaining the nitty-gritty of federated learning (FL) and how the FL method is helping to fulfill AI model optimization needs. The book also describes tools that vendors have created, including FL frameworks and platforms such as PySyft, Tensor Flow Federated (TFF), FATE (Federated AI Technology Enabler), Tensor/IO, and more. The first part of the text covers popular AI and ML methods, platforms, and applications, describing leading AI frameworks and libraries in order to clearly articulate how these tools can help with visualizing and implementing highly flexible AI models quickly. The second part focuses on federated learning, discussing its basic concepts, applications, platforms, and its potential in edge systems (such as IoT). Other topics covered include: - Building AI models that are destined to solve several problems, with a focus on widely articulated classification, regression, association, clustering, and other prediction problems- Generating actionable insights through a variety of AI algorithms, platforms, parallel processing, and other enablers- Compressing AI models so that computational, memory, storage, and network requirements can be substantially reduced- Addressing crucial issues such as data confidentiality, data access rights, data protection, and access to heterogeneous data- Overcoming cyberattacks on mission-critical software systems by leveraging federated learning Written in an accessible manner and containing a helpful mix of both theoretical concepts and practical applications, Model Optimization Methods for Efficient and Edge AI is an essential reference on the subject for graduate and postgraduate students, researchers, IT professionals, and business leaders.
