Jialun Song
Machine learning engineer at H&M Group. Prior to working, he has done his master thesis project at H&M Group on this exact topic - resource allocation for machine learning jobs.
Session
10-21
11:00
25min
Dynamic resource allocation for machine learning jobs at H&M Group
Jialun Song, Amira DINARI
Live broadcast: https://www.youtube.com/watch?v=oBPNk5qN0L4
At H&M Group, we are increasingly adopting machine learning algorithms and rapidly developing successful use cases, one of the applications is a dynamic resources allocation (memory and cpu) using data driven analysis and ML to decrease the cost of infrastructure.
The objective of this talk is to show how one of H&M use cases adopted ML workflow using airflow, kubernetes and docker and how to solve the provisioning problem with ML approach.
Data Science, AI, and Machine Learning
Data