Sep 27, 2021
Federated learning is relatively new (less than five years old), but it stands to have a huge impact on the machine learning landscape, especially for healthcare. 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. Federated learning can be used for things like medical imaging, computer vision applications, natural language processing (NLP), and deep learning. Listen in to learn what federated learning is and why it matters, how it’s protecting sensitive data, how it’s different from other machine learning approaches, the many uses for federated learning, how data is annotated in federated learning, the cyber security concerns about federated learning, and what the future of federated learning looks like!
For more resources on federated learning, check out these links:
OpenFL: Intel open source federated learning library: https://github.com/intel/openfl
Federated Learning in Medicine: A Nature paper: https://www.nature.com/articles/s41598-020-69250-1
Intel Federated Learning Slack: https://join.slack.com/t/openfl/shared_invite/zt-ovzbohvn-T5fApk05~YS_iZhjJ5yaTw
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.