Short but comprehensive end-to-end pipeline demo using the https://Iguazio.com real-time data science platform. MLOps (also known as DevOps for machine learning) is the practice of collaboration and communication between data scientists and data engineers to help manage the production machine learning (ML) lifecycle. Presented by Yaron Haviv, CTO & Co-Founder of Iguazio — https://www.linkedin.com/in/yaronh/ All code is here: https://github.com/mlrun/demos
0:00 - Intro to MLOps
0:43 - MLOps Tasks
1:12 - ML Pipeline
2:07 - DEMO: Iguazio (https://www.iguazio.com/) Data Science Platform
2:37 - Jupyter Notebook
3:56 - Serverless Function Marketplace
5:03 - MLRun UI
5:52 - Automated KubeFlow Pipeline
8:27 - KubeFlow Graph
10:44 - Inferencing API Canary Deployment
11:45 - Monitor & Visualize (Grafana)
12:47 - Summary
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