MLOps.community Operationalize Open Source Models with SAS Open Model Manager // Ivan Nardini // Customer Engineer at SAS // MLOps Meetup #39
MLOps community meetup #39! Last week, we talked to Ivan Nardini, Customer Engineer at SAS, about Operationalize Open Source Models with SAS Open Model Manager.
Join the Community: https://go.mlops.community/YTJoinIn
Get the newsletter: https://go.mlops.community/YTNewsletter
// Abstract:
Analytics are Open.
According to their nature, Open Source technologies allow an agile development of the models, but this results in difficulty putting them in production. The goal of SAS is to support customers in operationalizing analytics. In this meetup, I present SAS Open Model Manager, a containerized Modelops tool that accelerates deployment processes and, once in production, allows monitoring your models (SAS and Open Source).
// Bio:
As a member of the Pre-Sales CI & Analytics Support Team, I specialized in ModelOps and Decisioning. I've been involved in operationalizing analytics using different open-source technologies in a variety of industries. My focus is on providing solutions to deploy, monitor, and govern models in production and optimize business decision-making processes. To reach this goal, I work with software technologies (SAS Viya platform, Container, CI/CD tools) and Cloud (AWS).
//Other Links you can check Ivan on:
https://medium.com/@ivannardini
----------- Connect With Us ✌️-------------
Join our Slack community:
https://go.mlops.community/slack
Follow us on Twitter: @mlopscommunity
Sign up for the next meetup:
https://go.mlops.community/register
Connect with Demetrios on LinkedIn:
https://www.linkedin.com/in/dpbrinkm/
Connect with Ivan on LinkedIn:
https://www.linkedin.com/in/ivan-nardiniDescription
Timestamps:
0:00 - Intro to Ivan Nardini
3:41 - Operationalize Open Source Models with SAS Open Model Manager slide
4:21 - Agenda
5:01 - What is ModelOps, and what is the difference between MLOps and ModelOps?
6:19 - "Do I look like an expert?" Ivan's Background
7:12 - Why ModelOps?
7:20 - Operationalizing Analytics
8:12 - Operationalizing Analytics: SAS
9:08 - Operationalizing Analytics: Customer
11:36 - What's a model for you?
12:07 - Hidden Complexity in ML Systems
12:52 - Hidden Complexity in ML Systems: Business Prospective
14:12 - Hidden Complexity in ML Systems: IT Prospective
17:12 - One of the hardest things is Security?
17:52 - Hidden Complexity in ML Systems: Analytics Prospective
19:20 - Why ModelOps?
20:09 - ModelOps technologies Map
22:29 - Customers ModelOps Maturity over Technology Propensity. MLOps Maturity vs. Technology Propensity
26:23 - Show us your Analytical Models
26:56 - SAS can support you to ship them in production, providing Governance and Decisioning.
27:28 - When you talk to people, is there something that you feel like there is a unified model, but you're focusing on the wrong thing?
29:14 - Have you seen Reproducibility and Governance?
30:47 - Advertising Time
30:55 - Operationalize Open Source Models with SAS Open Model Manager
31:02 - ModelOps with SAS
32:06 - SAS Open Model Manager
33:18 - Demo
33:27 - SAS Model Ops Architecture - Classification Model
35:02 - Model Demo: Credit Scoring Business Application
50:20 - Take Homes
50:24 - Operationalize Analytics
50:32 - Model Lifecycle Effort Side
51:20 - Business Value Side
51:47 - Typical Analytics Operationalization Graph
52:18 - Analytics Operationalization with ModelOps Graph
53:18 - Is this for everybody?