Snowflake ML

For these templates, you will need to install the SnowflakeML extension package.

Create a classification model

Snowflake
✅

This example shows how to create a pipeline to train a classification model using Snowflake ML, evaluate the model and use it for prediction. In particular, we will create a classification model to estimate customer churn for a telecom company in California.

This example workflow will help you see how telco companies can detect high-risk customers, uncover the reasons behind customer departures, and develop targeted strategies to boost retention and satisfaction by training a classification model.

Download this example

Create a forecasting model

Snowflake
✅

This template shows how to create a forecast model using Snowflake ML through the extension package for Workflows. There are three main stages involved:

• Training a model, using some input data and adjusting to the desired parameters,

• Evaluating and understanding the model and its performance,

• Forecasting and saving the results.

Download this example