Building ML Models in Snowflake Using Python UDFs and Snowpark | DEMO

Learn how to build machine-learning models in Snowflake in this demo by Sonny Rivera of Thoughtspot and Chris Hastie of InterWorks. During the demo, they show how to use Snowpark to clean your data and perform feature engineering, build and train sales forecast models using Python in Snowflake, use Python UDFs to expose your predictive models, and present and analyze your models in ThoughtSpot.

To access the code used in this demo, go to:

To access the Quickstart guide for this topic, go to:

Learn more about Thoughtspot:
Twitter: @thoughtsport

Learn more about Interworks:
Twitter: @interworks

To connect with the presenters:
Sonny Rivera, Senior Analytics Evangelist, ThoughtSpot

Chris Hastie, Data Engineering and Analytics Consultant, InterWorks

Learn how to build your application on Snowflake:

Continue the conversation by joining the Snowflake Community:

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[octo]

How would you solve this with a vectorized UDF?

Is there a demo on same.

[nagasai]

Where can i find the data set that is used in this video

[tahabekmez]

When you run the ml, does it run on local machine or within snowflake?

[saeedrahman]

if we do the per category training and predictions in udf function via pandas dataframe we wouldn't get any parallelization benefit, right ? We would process all the categories sequenetially.
Shouldn't we use UDTF for these kind of operations ?