Explore the world of Machine Learning Operations (MLOps) and Cloud AI in this insightful 43-minute conference talk by Google's Kaz Sato. Delve into the challenges of productionizing machine learning models and discover solutions for continuous deployment, performance optimization, and technical support. Learn about data validation techniques through a live demo, understand freshness requirements, and gain valuable insights into ML lifecycle management. Equip yourself with the knowledge to become an ML superhero and effectively tackle the complexities of implementing machine learning in production environments.
Productionizing ML with ML Ops and Cloud AI
Overview
Syllabus
Introduction
What is ML Ops
ML Superhero
Problems
Deep Running Continuous
Performance
Technical Support
Data Validation
Data Validation Demo
Freshness Requirements
ML Lifecycle Management
Summary
Taught by
Linux Foundation
