Operationalize Open Source Models with SAS Open Model Manager // Ivan Nardini // Customer Engineer at SAS // MLOps Meetup #39

MLOps.community - A podcast by Demetrios Brinkmann

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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.   // Abstract: Analytics are Open.   According to their nature, Open Source technologies allows an agile development of the models, but it results difficult to put them in production.  The goal of SAS is supporting customers in operationalize 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 Pre-Sales CI & Analytics Support Team, I'm 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 decisions 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 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?

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