Home Page Icon
Home Page
Table of Contents for
Federated Learning with Python
Close
Federated Learning with Python
by Kiyoshi Nakayama PhD, George Jeno
Federated Learning with Python
Federated Learning with Python
Acknowledgments
Contributors
About the authors
About the reviewer
Preface
Part 1 Federated Learning – Conceptual Foundations
Chapter 1: Challenges in Big Data and Traditional AI
Chapter 2: What Is Federated Learning?
Chapter 3: Workings of the Federated Learning System
Part 2 The Design and Implementation of the Federated Learning System
Chapter 4: Federated Learning Server Implementation with Python
Chapter 5: Federated Learning Client-Side Implementation
Chapter 6: Running the Federated Learning System and Analyzing the Results
Chapter 7: Model Aggregation
Part 3 Moving Toward the Production of Federated Learning Applications
Chapter 8: Introducing Existing Federated Learning Frameworks
Chapter 9: Case Studies with Key Use Cases of Federated Learning Applications
Chapter 10: Future Trends and Developments
Appendix: Exploring Internal Libraries
Index
Other Books You May Enjoy
Search in book...
Toggle Font Controls
Playlists
Add To
Create new playlist
Name your new playlist
Playlist description (optional)
Cancel
Create playlist
Sign In
Email address
Password
Forgot Password?
Create account
Login
or
Continue with Facebook
Continue with Google
Sign Up
Full Name
Email address
Confirm Email Address
Password
Login
Create account
or
Continue with Facebook
Continue with Google
Next
Next Chapter
Federated Learning with Python
Add Highlight
No Comment
..................Content has been hidden....................
You can't read the all page of ebook, please click
here
login for view all page.
Day Mode
Cloud Mode
Night Mode
Reset