[DevOpsDays Atlanta] The Shallow End of Deep Learning

Massive LLMs take huge amounts of data to train and datacenters to run. You have some trend data from your services, and maybe it would be kinda interesting to have some way to do some predictions or projections off that data. How far could you get with some Python and a Jupyter notebook?

Far enough to be dangerous in your next production performance meeting. In this talk, we’ll wade into the shallow end of the deep learning tools ecosystem and talk through data practices for getting your own insights out of small AI projects.

Mandi Walls is a DevOps Advocate on the Community and Advocacy Team at PagerDuty. Before joining PagerDuty, Mandi spent a number of years at Chef Software, working with customers and community members in the US and Europe. Originally a large-scale systems administrator, Mandi has focused on IT automation; organizational culture and change; and community.