Explore high-level MLOps concepts and practices in this 34-minute video featuring Microsoft data scientists. Gain insights from an AI Taskforce as they discuss use cases, common challenges from data engineering, machine learning engineering, and data science perspectives, and define success in MLOps. Learn about surprising customer challenges and how to avoid them, understand MLOps principles, and receive valuable tips from industry professionals. Discover the role of MLOps in delivery missions and gain a comprehensive understanding of this crucial aspect of AI and machine learning implementation.
High-Level Introduction to MLOps - AI Show Episode 33
Overview
Syllabus
AI Show Intro.
Welcome and Introductions.
Use cases from the AI Taskforce.
Commonalities across projects.
Common challenges - from the Data Engineer perspective.
Common challenges - from the ML Engineer perspective.
Common challenges - from the Data Science perspective.
What does success in MLOps look like?.
Surprising challenges working with customers and how to avoid them.
Review - what is ML Ops.
MLOps in Delivery mission.
MLOps principles.
Tips from the pros .
Taught by
Microsoft Developer
