Easy access to relevant, safe data is a major bottleneck hindering developers and data scientists. But what if you could generate your own accurate, privacy-protected, shareable data?
Synthetic data can provide an inexpensive alternative to real sets of data that can’t be used due to its sensitivity or regulations. Such data is used for training machine learning models, testing, and performing quality assurance.
In this webinar with Mason Egger, we’ll learn about using Synthetic Data, and we’ll learn how to get started creating our own Synthetic Data.
Join us on July 29th, 2022 at 5:00 pm CEST
About the speaker
Mason Egger
Mason is currently a Developer Advocate at Gretel.ai who specializes in cloud infrastructure, distributed systems, Python and Data Science. Prior to his work at Gretel, he was a Developer Advocate at Digital Ocean. His prior experience also includes being an SRE who helps build and maintain a highly available hybrid multicloud PaaS.
He is an avid programmer, speaker, educator, and writer/blogger. He contributes to random open source projects here and there and in his spare time he enjoys reading, camping, kayaking, and exploring new places.
