Publisher description
- Covers all major aspects of federated learning in various applications. - Presents the framework and important key aspects of federated machine learning. Major use cases like healthcare, industrial automation, blockchain and IoT are discussed in this book. - Includes a wide variety of topics, thus offers readers multiple perspectives on a variety of disciplines included in a number of chapters
More books by the authors
Similar booksFederal Reserve, Including: Federal Reserve System, Federal Reserve ACT, Federal Reserve Bank, Federal Reserve Note, Samuel P. Bush, Automated Clearing House, Federal Open Market Committee, Taylor Rule, Check 21 ACT, Prime Rate, Federal Funds RateeBook 2023
Rate the book
Write a review and share your opinion with others. Try to focus on the content of the book. Read our instructions for further information.
Handbook on Federated Learning
Book reviews » Handbook on Federated Learning
|
|
![Handbook on Federated Learning](/images/background.gif) |
![Handbook on Federated Learning](/images/background.gif) |
|
|
|