What That Means with Camille: Federated Learning

Ngarama

25 min

Knowledge

Description

Federated learning is relatively new, but it stands to have a huge impact on the machine learning landscape, especially as it applies to healthcare. On today’s episode of What That Means, Camille is joined by Olga Perepelkina, PhD, a Deep Learning Product Manager at Intel, to find out exactly how this field is projected to change the world. They cover: - What federated learning is and why it matters - How it’s helping to protect sensitive data - How it differs from other machine learning approaches - The various ways federated learning can be used - How data is annotated in federated learning, and why it sometimes lacks quality control - Which components of the federated learning model are vulnerable to cyberattacks, as well as possible solutions to boost security - Whether or not you can have different kinds of input with the federated learning model - What the future holds for federated learning ...and more Great conversation, don’t miss it! The views and opinions expressed are those of the guests and author and do not necessarily reflect the official policy or position of Intel Corporation. Here are some key take-aways: - At less than five years old, federated learning is a completely new area of research in machine learn

Uploader

josie.shore

Episodes

What That Means with Camille: Federated Learning

Ngarama

25:30