Federated Learning: Principles, Paradigms, and Applications
| PUBLISHER | Apple Academic Press (09/20/2024) |
| PRODUCT TYPE | Hardcover (Hardcover) |
Description
Explains federated learning and how it integrates AI technologies allowing multiple collaborators to build a robust machine-learning model using a large dataset. Describes benefits of federated learning, covering data privacy, data security, data access rights etc. Analyses common challenges, and attack strategies affecting FL systems.
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Product Format
Product Details
ISBN-13:
9781774916384
ISBN-10:
177491638X
Binding:
Hardback or Cased Book (Sewn)
Content Language:
English
More Product Details
Page Count:
334
Carton Quantity:
16
Product Dimensions:
6.14 x 0.81 x 9.21 inches
Weight:
1.48 pound(s)
Feature Codes:
Illustrated
Country of Origin:
US
Subject Information
BISAC Categories
Computers | Computer Engineering
Computers | Data Science - General
Computers | Artificial Intelligence - General
Descriptions, Reviews, Etc.
publisher marketing
Explains federated learning and how it integrates AI technologies allowing multiple collaborators to build a robust machine-learning model using a large dataset. Describes benefits of federated learning, covering data privacy, data security, data access rights etc. Analyses common challenges, and attack strategies affecting FL systems.
Show More
List Price $200.00
Your Price
$198.00