1. Moscone West 2000

Machine learning algorithms are key to modern at-scale cyber-defense. Transfer learning is a state of the art ML paradigm that enables applying knowledge and algorithms developed from one field to another, resulting in innovative solutions. This talk will present transfer learning in action wherein techniques created from other areas are successfully re-purposed and applied to cybersecurity.

Learning Objectives:
1: Learn how ML models can be applied to cybersecurity.
2: Discover how models developed in other domains apply to cybersecurity.
3: Get ideas for how to apply ML to your own cyber-defense.

Participants: