You’ve Got a Data Science Team, Now What?
Let's talk about what your machine learning (ML) journey looks like so far.
The promise of a data science revolution felt like it was right there, within your grasp. You recruited a smart team, established sophisticated governance and constructed a common repository for your data. Even with all these investments, you still find it hard to put models into production and continuously update and monitor them.
Sound familiar? We’ve heard it time again from our clients, so we wanted to share our experience and highlight how MLOps can help scale your end-to-end data science process. If you feel seen after watching this video, this could be the next step you’ve been looking for.
Check out more of our AI articles to learn about MLOps and how your team can get started — or go ahead and schedule an MLOps Platforming Briefing.
