Hyperparameter Tuning in Snowpark

Hyperparameter tuning for your machine learning models can take hours. But with Snowpark User-Defined Table Functions (UDTFs), you can parallelize these models so that they run in a fraction of the time, giving data scientists the ability to finely tune their models. Chase Romano, Data Scientist at Snowflake, demonstrates how to tune hyperparameters and turn them into objects that can then be fed into your model for optimized performance.

[TusharKale]

Thank you for sharing Romano. It was very useful