Explore Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Free Learning

Federated Learning with Python

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

View More author details

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

Why subscribe?

15. Other Books You May Enjoy

Appendix: Exploring Internal Libraries

Case Studies with Key Use Cases of Federated Learning Applications

Federated learning (FL) has met with a variety of AI applications so far in various contexts and integration has been explored with trials and errors in those fields. One of the most popular areas has been in the medical and healthcare fields where the concept of privacy-preserving AI naturally fits with the current needs and challenges of healthcare AI. FL has also been applied to the financial services industry, edge computing devices, and the Internet of Things (IoT), through which FL has been shown to have significant benefits in quite a few applications, which will resolve many important social problems.

In this chapter, we will be discussing some of the major use cases of FL in different fields. It is our hope that by the end of this chapter, you’ll be familiar with some of the applications of FL in different industries. We'll start by exploring the use of FL in the healthcare and financial industries...

The rest of the chapter is locked

Register for a free Packt account to unlock a world of extra content!

A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.

Unlock this book and the full library FREE for 7 days

Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of

Start free trial

Renews at $19.99/month. Cancel anytime

Authors (2)

Kiyoshi Nakayama, PhD

Kiyoshi Nakayama, PhD

Kiyoshi Nakayama, PhD, is the founder and CEO of TieSet Inc., which leads the development and dissemination of one of the most advanced distributed and federated learning platforms in the world. Before founding TieSet, he was a research scientist at NEC Laboratories America, renowned for having the world's top-notch machine learning research group of researchers. He was also a postdoctoral researcher at Fujitsu Laboratories of America, where he implemented a distributed system for smart energy. He has published several international articles and patents and received the best paper award twice in his career. Kiyoshi received his PhD in computer science from the University of California, Irvine.

See other products by Kiyoshi Nakayama, PhD

George Jeno

George Jeno

George Jeno is a co-founder of TieSet Inc. and has been a tech lead for the development of the STADLE federated learning platform. He has a deep understanding of machine learning theory and system architecture design, and he has leveraged this knowledge to research new algorithms and applications for distributed and federated learning. He holds a master's degree in computer science (with a specialization in machine learning) from Georgia Tech.

See other products by George Jeno

Personalised recommendations for you

Based on your interests and search pattern

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m