Snowpark for Python, now generally available, empowers the growing Python community of data scientists, data engineers, and developers to build secure and scalable data pipelines and machine learning (ML) workflows directly within Snowflake—taking advantage of Snowflake’s performance, elasticity, and security benefits, which are critical for production workloads.

Using user-defined table functions (UDTFs) and the new Snowpark-optimized warehouse with higher memory, users can run large-scale model training workloads using popular open-source libraries available through Anaconda integration.

See how you can execute forecast for 200 retail stores in parallel using XGBoost. Find more information here: http://snowflake.com/snowpark

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