hands-on lab
Drawing Insights with BigQuery ML
Difficulty: Intermediate
Duration: Up to 1 hour
Students: 253
Rating: 3.6/5
Get guided in a real environmentPractice with a step-by-step scenario in a real, provisioned environment.
Learn and validateUse validations to check your solutions every step of the way.
See resultsTrack your knowledge and monitor your progress.
Description
Machine learning is proving to be very powerful in gathering insights with your data. BigQuery ML allows the user to perform Machine Learning training, evaluation, and prediction on large sets of data. This lab will explain some of the basic concepts along with an example of training a linear regression and binary logistic regression model.
Learning Objectives
Upon completion of this lab you will be able to:
- Utilize BigQuery ML to train, evaluate and predict with a linear regression model
- Utilize BigQuery ML to train, evaluate and predict with a binary logistic regression model
- Visualize a BigQuery ML Dataset
Intended Audience
This lab is intended for:
- Data engineers
- Anyone interested in gaining insights from BigQuery ML
Prerequisites
You should possess:
- A basic understanding of BigQuery ML
- A basic understanding of data engineering concepts
Updates
November 8th, 2024 - Updated the weather station data set
August 7th, 2024 - Added password protection to notebook
Covered topics
Lab steps
Starting the Lab's Google Cloud Hosted Jupyter Notebook