DEMO: Using Snowflake Snowpark As Part Of Your Machine Learning Workflow

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In this session, we’ll explore exciting new Snowpark enhancements, walk you through demos of these new capabilities, and help you see what new use cases could open up within your organization.

Teams working on data science initiatives are tasked with deriving new insights from massive amounts of data. To accomplish this, teams work with compute environments that require heavy operational overhead, which means most of their time is spent extracting and processing features for machine learning model training and inference. Pairing Snowflake’s near-unlimited access to data and elastic processing engine with the most popular programming languages can change that, so data scientists can spend more time on model development.

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