Register once to get access to both webinars!*

Scalable data science practices are built on the foundation of effective data management and access to the right data at the right time to feed data-hungry machine learning (ML) models. By accelerating the steps associated with accessing and processing all relevant data and providing seamless connectivity to best-of-breed ML platforms, Snowflake enables data scientists to spend more time on what matters most: building models that generate actionable business insights.

Through this two-part series, experts will teach you best practices for features that can significantly speed up your ML workflows with timely access to data while also delivering results to your organization with the models you build and deploy.

Part I: How to use Snowflake Native Connectors for Machine Learning

Attend this webinar to learn how to:

  • Use Pandas DataFrames with the Snowflake Connector for Python
  • Use advanced features in the Snowflake Connector for Spark
  • Use Snowflake with R in your favorite IDE

 

Part II: How to use Snowflake for Machine Learning Model Inference

Attend this webinar to learn how to:

  • Use Snowpark to build scalable pipelines¬†
  • Communicate with externally hosted models with external functions
  • Deploy models inside Snowflake with UDFs
  • Deliver model results to business users and data applications

*By completing the form you will automatically be registered for both webinars listed above. If you wish to register for individual webinars, click on the Learn More links associated with each webinar.

Speakers
  • Michael Gregory

    Field CTO for Data Science and ML

  • Sathish Gangichetty

    Field CTO for Data Science and ML

  • Chase Ginther

    Field CTO for Data Science and ML

  • Rishu Saxena

    Field CTO for Data Science and ML

SAVE YOUR SEAT