GitLab / GitLab Group Kickoffs - ModelOps

This is a very early demo for the POC of model registry

Modelops

Speakers: David Desanto (Sr. Director, Dev, Sec, ModelOps), Taylor McCaslin (Product Manager, ModelOps), Mon Ray (Engineering Manager, ModleOps)
In this session, we will discuss the three pillars of ModelOps, including how to integrate Data Science into DevOps. This will include a brief history of how we got here, as well as where we are going. We're cover the personas of Modelops customers and explore how we'll integrate ModelOps into GitLab.

Chapters:
0:00 Talk introduction
1:01 David Desanto: What the ML is up with DevOps and AI?
2:02 So... What the ML is ModelOps?
7:04 ModelOps of Tomorrow
14:23 Taylor McCaslin: The People behind Data Science
19:38 Data Science Jobs to Be Done
23:23 The Tools of Data Scientists
27:02 The challenges of handoffs
28:38 Mon Ray: Applied ML - How does UnReview work?
31:41 The Full ML Stack
35:45 Challenges building ML models
37:10 The Applied ML Team
38:48 David Desanto: The ModelOps Stage
39:45 We're Hiring!

Please note, since this video was recorded "GitLab Learn stage" was renamed "Gitlab ModelOps stage"

Watch Sr. Director of Product David DeSanto and Principal Product Manager Taylor McCaslin discuss an overview of the Gitlab Learn stage, dig into the focus for each group, and answer common questions about this new area of investment for GitLab.

Links:
GitLab Learn Direction - https://about.gitlab.com/direction/modelops/
DataOps Direction - https://about.gitlab.com/direction/modelops/dataops/
MLOps Direction - https://about.gitlab.com/direction/modelops/mlops/
Applied ML Direction - https://about.gitlab.com/direction/modelops/applied_ml/

Join us in GitLab slack:
g_machine-learning: https://gitlab.slack.com/archives/C01ESHPNHS9
s_learn: https://gitlab.slack.com/archives/C01F1R4J7FW