Predict home prices using machine learning

DEMO

Build a machine learning model to predict home prices using scikit-learn and Snowpark

In this demo, we’ll show you how to build a machine learning model to predict home prices. We’ll walk you through setting up your Snowflake environment, preparing the raw data using Snowpark, training the model with scikit-learn, and deploying it as a Snowpark User Defined Function (UDF). Here’s a brief look at some of the things you’ll do:

• Use Snowpark to ingest raw data from a local file system into Snowflake
• Use Snowpark Python DataFrames to perform data transformations, such as group by, aggregate, pivot, and join to prep the data for downstream applications
• Prepare data and run ML training in Snowflake using scikit-learn
• Deploy the model as a Snowpark User Defined Function (UDF) using the integrated Anaconda package repository