Using Snowpark For Python To Build ML Workflows: A Hands-On Lab

In this hands-on lab, Snowflake ML Learning and AI Architect Caleb Baechtold provides a detailed explanation of the inner workings of Snowpark for Python before diving into an interactive lab in which you learn how data teams can go from data and feature engineering to ML model development and productionalizing in a collaborative and scalable way using Snowpark, Apache Airflow, Anaconda, and Streamlit. Prior experience using Python and data science tools such as notebooks and open-source packages is a plus.
Before you dive in, be sure to have the Getting Started with Snowpark for Python Quickstart in hand so you can follow along with the lab.
Link to Quickstart:
quickstarts.snowflake.com/gui...
Link to GitHub Repo:
github.com/Snowflake-Labs/sfg...
Connect with Caleb Baechtold from Snowflake:
LinkedIn: www.linkedin.com/in/caleb-baechtold
Learn how to build your application on Snowflake:
developers.snowflake.com
Continue the conversation by joining the Snowflake Community:
community.snowflake.com
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[@rakesh7464]

More of these types hands on-labs please!! These are great!

[@snowflakedevelopers]

Noted! Thank you so much for the feedback @rakesh7464!

[@Klayhamn]

Great presentation, thanks.

[@vishnuraj4409]

Thanks for amazing content. Quick qtn: is there is quick start guide to do all these in snowflake python worksheet instead of sagemaker or jupyter notebook

[@snowflakedevelopers]

Not at the moment, but thank you for your feedback. We are working on making the Quickstarts even easier for you to get started with!

[@rakesh7464]

Can past in the link for the github repository here please?

[@snowflakedevelopers]

Yep, here it is: github.com/Snowflake-Labs/sfguide-citibike-ml-snowpark-python. It's also been added to the video description, along with the Quickstart that goes along with it.