The Worst Game of Telephone Ever
Telephone is the party game where a phrase is whispered from the first player to the last until it spoken out loud to reveal how much the message has changed in transit. Data scientists often create models in R, excel, or even with pencil on paper. What happens when these models and algorithms are handed off to a development team to implement? How often is the final product actually doing what was originally intended? Is this the worst game of telephone ever? Can devOps practices help avoid these problems? What can data science & machine learning do for devOps? Please join Chris Corriere, a devOps advocate with SJ Technologies, as he shares stories about failure, success, trust, communication, Nash games, automation, and machine learning.
Map Reduce for Prioritizing a Backlog The Prisoners' Dilemma & The Stag Hunt The Difference between Complicated & Complex Domains Moving from Maps to Models devOps Dojo Practices for Machine Learning
Chris Corriere has been working with data, phones, networks and writing software for over twenty years. His background in mathematics and engineering has allowed him to adapt to new and industry-specific technologies and provided many unique consulting opportunities. As a devOps professional Chris is committed to culture, automation, learning, sharing, and having a good time while getting work done. Chris is currently a senior devOps advocate with SJ Technologies focused on dojo practices, mapping, & complexity science.