Training and Ensuring Reliability of ML Models - The Power of ArgoCD, Flyte, and Argo Workflows
CNCF [Cloud Native Computing Foundation] via YouTube
Overview
Explore the practices implemented by Wolt to train and maintain ML models in this 25-minute conference talk. Discover how ArgoCD, Flyte, and Argo Workflows are utilized to create a streamlined, automated process for training, testing, and deploying reliable machine learning models. Learn about the challenges of ensuring consistency during training and deployment phases, and how these tools provide a unified platform for collaboration between Data Scientists and ML teams. Gain insights into Wolt's ML platform, including visual reports, active users, accessions, workflows, and use cases. Understand the importance of model reliability and the various tools available to achieve this goal in the context of a technology company known for its local commerce platform.
Syllabus
Introduction
About Wolt
Use Cases
ML Platform
ArgoCD Flyt
Argo workflows
Visual reports
Active users
accessions
workflows
use case
future work
Question
Taught by
CNCF [Cloud Native Computing Foundation]