SQL and Python are both powerful on their own, but their value in modern data science and machine learning is highest when they work together. In the past, leveraging both required working with separate development interfaces and separate infrastructure for each language. Using Snowflake and Hex, data science and other data teams can build and deploy models without complex IDE or infrastructure management for separate languages.  

Join us for this hands-on lab where where we’ll walk through a time series forecast demo using XGBoost, and you will learn how to:

  • Eliminate worries about development environment memory limits with SQL and Python execution in Snowflake’s elastic performance engine
  • Train and deploy ML models using Snowpark for Python and its integrated open-source libraries
  • Leverage Snowpark user defined table functions (UDTFs) to scale-out processing for 100s of models

Sprecher
  • Julian Forero

    Senior Product Marketing Manager at Snowflake

  • Chase Romano

    Solutions Architect, Data Science at Snowflake

  • Ariel Zahler Harnik

    Head of Partnerships at Hex

  • Gabe Flomo

    Developer Advocate at Hex

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