After AI/ML models are developed, the challenge is continuously operating them in production on changing data. Snowflake’s MLOps capabilities include a native model registry that makes it easy to manage models and features in production for faster time to insights. INVISTA, a Koch Industries subsidiary, uses Snowflake to build and operationalize ML models for manufacturing chemicals, polymers, fabrics and fibers.
Watch this session with customer INVISTA and ML experts to learn more about how to use Snowflake to:
- Leverage the Snowflake Model Registry to maintain a centralized repository of models and metadata, complete with role-based access controls
- Use Python to operationalize ML in your pipelines by using Snowflake Tasks with DAG views
- Benefit from a unified MLOps solution for faster management of features and models
Speakers
Earl Carlisle
Data Science Leader
INVISTA
Vamshi Sai Mugala
Senior Data Scientist
INVISTA
Kirk Mason
Solution Innovation
Consultant - AI/ML
Snowflake
Tyler White
Solution Innovation
Architect - AI/ML
Snowflake
Lucy Zhu
Product Marketing Manager
Snowflake