Explore federated learning, a revolutionary approach to machine learning that enables AI training across devices without centralizing data, in this 31-minute video tutorial. Discover how this technique enhances privacy while feeding data-hungry models. Join Daniel J. Beutel, co-creator of Flower, an open-source framework used by Fortune 500 companies and top universities, as he guides you through the fundamentals of federated learning. Gain insights into why federated learning is crucial, understand the concept of data richness in AI, and learn about Flower Federations. Participate in a hands-on "Hello, Flower" tutorial to get practical experience. Perfect for those interested in machine learning, data science, and AI applications, this session provides a comprehensive introduction to federated learning and its potential to reshape the AI landscape while protecting sensitive data.
Introduction to Federated Learning with Flower - A Hands-on Tutorial
Overview
Syllabus
- Introduction
- Why Federated Learning?
- Are we data-poor?
- What would data-rich AI look like?
- Federated Learning 101
- Hands-on: Hello, Flower
- Flower Federations
- Next Steps
- Questions
Taught by
Open Data Science
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