Features are at the core of machine learning use cases. Yet, most of the biggest challenges for enterprises today include: getting a wide spectrum of data types in the right format and just in time for both model training and model inference, making features discoverable and reusable, and doing so in a way that allows you scale your AI/ML initiatives and speed up the iterations.
Join us for a Snowflake point of view on:
- Feature store and how to use Snowflake as the store and engine for your feature platform
- Best practices on how to build your own or leverage pre-built open-source or commercial solutions
- Deep dives on key enabling features that enable a single platform architecture
Technical Director Snowflake, Snowflake
Sr Partner Sales Engineer, AI & ML, Snowflake
Senior Product Marketing Manager, Snowflake