In this episode of MLOps Live, Piotr is joined by Aurimas Griciūnas, a Senior Solutions Architect at neptune.ai. Aurimas elaborates on the distinctions between machine learning (ML) platforms and data platform teams and the advantages of automating an ML stack. He also went over the process normalization requirements for streamlined teams from data platform and ML platform groups. Aurimas explains why data platforms are primarily concerned with displaying results, whereas ML platforms are centered on the frameworks and tooling that machine learning professionals use on a daily basis.

In this episode of MLOps Live, Piotr is joined by Aurimas Griciūnas, a Senior Solutions Architect at neptune.ai. Aurimas elaborates on the distinctions between machine learning (ML) platforms and data platform teams and the advantages of automating an ML stack. He also went over the process normalization requirements for streamlined teams from data platform and ML platform groups. Aurimas explains why data platforms are primarily concerned with displaying results, whereas ML platforms are centered on the frameworks and tooling that machine learning professionals use on a daily basis.