Using Snowpark As Part Of Your Machine Learning Workflow
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 more time can be spent on model development.