You're reading from Federated Learning with Python Design and implement a federated learning system and develop applications using existing frameworks

Product type Paperback

Published in Oct 2022

Publisher Packt

ISBN-13 9781803247106

Length 326 pages

Edition 1st Edition

Languages

Python

Tools

Federated Learning

Concepts

Design

Authors (2):

George Jeno

Kiyoshi Nakayama, PhD

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Table of Contents (17) Chapters

Preface

1. Part 1 Federated Learning – Conceptual Foundations

2. Chapter 1: Challenges in Big Data and Traditional AI FREE CHAPTER

3. Chapter 2: What Is Federated Learning?

4. Chapter 3: Workings of the Federated Learning System

5. Part 2 The Design and Implementation of the Federated Learning System

6. Chapter 4: Federated Learning Server Implementation with Python

7. Chapter 5: Federated Learning Client-Side Implementation

8. Chapter 6: Running the Federated Learning System and Analyzing the Results

9. Chapter 7: Model Aggregation

10. Part 3 Moving Toward the Production of Federated Learning Applications

11. Chapter 8: Introducing Existing Federated Learning Frameworks

12. Chapter 9: Case Studies with Key Use Cases of Federated Learning Applications

13. Chapter 10: Future Trends and Developments

14. Index

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15. Other Books You May Enjoy

Appendix: Exploring Internal Libraries

Technical requirements

You can find the supplemental code files for this chapter in the book’s GitHub repository:

https://github.com/PacktPublishing/Federated-Learning-with-Python

Important note

You can use the code files for personal or educational purposes. Please note that we will not support deployments for commercial use and will not be responsible for any errors, issues, or damage caused by using the code.

Each implementation example in this chapter was run on an x64 machine running Ubuntu 20.04.

The implementation of the training code for the NLP example requires the following libraries to run:

Python 3 (version ≥ 3.8)
NumPy
TensorFlow (version ≥ 2.9.1)
TensorFlow Hub (pip install tensorflow-hub)
TensorFlow Datasets (pip install tensorflow-datasets)
TensorFlow Text (pip install tensorflow-text)

Using a GPU with the appropriate TensorFlow installation is recommended to save training time for the NLP example...

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You're reading from Federated Learning with Python Design and implement a federated learning system and develop applications using existing frameworks

Table of Contents (17) Chapters

Technical requirements

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Authors (2)

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