Privacy-friendly machine learning data sets: synthetic data
Statistically-relevant data, but not actually exploitable.
Privacy is a moving target. Here’s how engineering teams can stay on track (Ep. 453)
On this sponsored episode of the podcast, we talk with Rob Picard and Matt Cooper of Vanta.
Using synthetic data to power machine learning while protecting user privacy
On this episode, we talk to John Myers, CTO and cofounder of Gretel, a company that provides synthetic data for training machine learning models without exposing any of their customers personally identifiable information.
Privacy is an afterthought in the software lifecycle. That needs to change.
The key to combining privacy and innovation is baking it into the SDLC. Analogous to application security's (AppSec) upstream shift into the development cycle, privacy belongs at the outset of development, not as an afterthought. Here's why.