hands-on lab
Machine Learning and BigQuery GIS
Difficulty: Intermediate
Duration: Up to 1 hour
Students: 123
Rating: 5/5
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Description
This lab demonstrates how to perform a clustering analysis in BigQuery GIS using Python and Jupyter notebooks. The lab leverages the built-in DBScan clustering function in BigQuery GIS to cluster street trees in San Francisco from the Google public datasets. It also shows how to analyze the cluster results using the pandas library within Python.
Learning Objectives
Upon completion of this lab you will be able to:
- Interact with BigQuery GIS datasets within Jupyter notebooks
- Perform a clustering analysis on
GEOGRAPHYdata - Use
pandasto analyze cluster analysis results
Intended Audience
This lab is intended for:
- GIS engineers
- Data engineers dealing with location-based data
- Developers looking to leverage geospatial information
- Data scientist leveraging geospatial data
Prerequisites
You should possess:
- Basic understanding of relational databases and ANSI SQL
- Basic understanding of Python
- Familiarity with BigQuery GIS's
GEOGRAPHYdatatype
Updates
August 7th, 2024 - Added password protection to notebook
Covered topics
Lab steps
Starting the Lab's Google Cloud Hosted Jupyter Notebook