In this session we will perform a full exploration of the Snowpark ML Toolkit using dbt Python models on the dbt Cloud without any package installation. You will learn how Snowflake improves on familiar ML libraries like Scikit-Learn and XGBoost to make them scale within its scalable runtime.
During this session you will:
- Start with 50,000 rows and scale to 50 million rows on various data transformations with the toolkit
- Train and predict a dbt Python model with XGBoost
- Switch between SQL and Python transformations in a pipeline where dbt takes care of the boilerplate code when pushing to Snowflake