

Federated Learning with Mike Lee Williams
Oct 23, 2020
Chapters
Transcript
Episode notes
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Introduction
00:00 • 3min
How to Mask Information in Machine Learning
03:00 • 2min
The Differential Privacy Approach to Solving an Income Problem
05:13 • 3min
The Evolution of Machine Learning
08:06 • 3min
Differential Privacy: How to Avoid Touching Your Data
11:12 • 3min
Federated Learning: A Way to Get Around Access to Data
13:45 • 5min
Google's Use Case for Federated Learning
18:24 • 3min
Federated Learning and the Future of Active Research
21:15 • 2min
Federated Averaging: A New Approach to Distributed Systems
23:15 • 3min
Federated Learning: A Sexy Modern Machine Learning Technology
26:13 • 3min
Federated Learning and Neural Networks
29:03 • 3min
PySift and TensorFlow Federated: A Comparison
31:40 • 3min
How to Minimize Bandwidth Concerns on Your Phone
34:34 • 2min
How to Use Federated Learning to Protect Your Data
36:43 • 5min
The Future of Healthcare in Europe
41:15 • 3min
The Future of Federated Learning
44:27 • 4min