Streamline MLOps with Snowflake and Posit

See an end-to-end demo of deploying Scikit-learn models using Lending Club data to optimize your production workflow.
Play video Deploying Scikit-learn models for in-database scoring with Snowflake and Posit Team

Table of Contents

  1. Intro to Orbital
  2. Running Positron within Snowflake
  3. Connect to the data
  4. Feature engineering and model fitting pipeline with scikit-learn
  5. Save model to Snowflake model registry
  6. Parsing the sci-kit learn pipeline with Orbital to convert to SQL
  7. Model predictions for 2.25 million rows in Snowflake in less than 5 seconds
  8. Create a Snowflake view (saved SQL query)
  9. What Orbital can & can't do
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Intro to Orbital

For converting models to SQL to run predictions inside databases

 

Running Positron within Snowflake

Positron in Posit Workbench as a native app within Snowflake

 

Connect to the data

Loan dataset from LendingClub.

 

Feature engineering and model fitting pipeline with scikit-learn

 

Save model to Snowflake model registry

 

Parsing the sci-kit learn pipeline with Orbital to convert to SQL

 

Model predictions for 2.25 million rows in Snowflake in less than 5 seconds

 

Create a Snowflake view (saved SQL query)

 

What Orbital can & can't do

 

Save your seat for our monthly demo series

We host these Workflow Demos the last Wednesday of every month, and you can add them to your calendar with this link.