Adopt ModelOps within DevOps to solve data science challenges

This post introduces the ModelOps stage within GitLab, which aims to integrate data science workloads into the existing DevOps platform. It breaks down ModelOps into three primary groups: DataOps (data fetching, cleaning, processing), MLOps (building, testing, training, and deploying AI/ML models), and AI Assisted (enriching existing GitLab features with ML). It details the user personas and challenges associated with each group, emphasizing the goal of enabling data science workloads and empowering customers to build and integrate them within GitLab applications.