Feature Store Observability: What it is, and why it matters
Aman will discuss the state of ML production monitoring, its challenges, and how to actively improve models and features in production.
Aman will discuss the state of ML production monitoring, its challenges, and how to actively improve models and features in production.
Machine learning models have become increasingly complex, and it is imperative to utilize better tools to monitor, troubleshoot, and explain their decisions as models move from research to production environments. Feature stores are a common part of the ML platform stack for many teams - however, should a feature store be monitored? Aman, Group product manager at Arize AI, will discuss the state of ML production monitoring, its challenges, and how to actively improve models and features in production.
