# ML Pipeline with Snowpark & Snowflake

***

## Overview

This example demonstrates:

* Running Snowpark jobs from Valohai
* Training and deploying models within Snowflake
* Visualizing predictions in Snowpark Container Service

***

### Steps

{% stepper %}
{% step %}
**Data Loading**

Load the data from a CSV to a Snowflake table called `SOURCE_OF_TRUTH`.
{% endstep %}

{% step %}
**Model Training**

Use the loaded data to train and test a model to predict insurance charges.
{% endstep %}

{% step %}
**Mock Streaming Data**

Use the some of the data in `INCOMING_DATA_SOURCE` and insert it to `LANDING_TABLE` to mock the process of data coming in.
{% endstep %}

{% step %}
**Running Inference**

Use the model to run inference on incoming data and save results.
{% endstep %}

{% step %}
**Deploy a Streamlit app to Snowpark Container Service**

Trigger a long running service in Snowpark Container Service to host the Streamlit app.
{% endstep %}
{% endstepper %}

***

### GitHub Repository

The repository walks you through the steps above:

{% embed url="<https://github.com/valohai/snowpark-example>" %}


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