MLOps Collaboration
MLOps is not just about engineering; it thrives on collaboration with data scientists and engineers to streamline processes. By templating infrastructure, teams can focus on model and data variations without redundant retooling. This approach positions MLOps as internal advocates, creating tools that empower data scientists to efficiently implement solutions like streaming recommendation services.In this clip
From this podcast
Super Data Science: ML & AI Podcast with Jon Krohn
SDS 599: MLOps: Machine Learning Operations — with @Miki_ML
Related Questions
What are the essential roles in a data team as discussed in the episode Building for Small Data Science Teams // James Lamb // MLOps Coffee Sessions #69 and the clip Balancing Data Science and Data Engineering?
What does a machine learning engineer do in the context of the episode Building for Small Data Science Teams // James Lamb // MLOps Coffee Sessions #69 and the clip Machine Learning Engineer Insights?