One of the biggest challenges in AI/ML is stitching together multiple solutions to deploy and scale models in production. Snowflake is accelerating the path from model development to production with Snowpark ML, the Python library and underlying infrastructure for end-to-end ML workflows in Snowflake. Snowpark ML can accelerate your existing model development and operations processes seamlessly by easily integrating with the most popular existing AI/ML platforms and notebooks.
Join this session with our product leader, Sandeep Gupta to learn more about top ML architectures with Snowflake and hear about:
- Benefits of developing and operationalizing features and models using a unified governance framework
- Common AI/ML reference architectures for integrating Snowpark ML with cloud provider platforms (e.g. Azure ML) and notebook of choice
- How to get started with Snowpark ML
Senior Product Manager
Sr. Architect, Machine Learning Field CTO
Sr. Partner Sales Engineer, Data Science