As part of its effort to gain a larger market share in the cloud computing market, Google Cloud has been adding powerful tools to its platform, especially around AI. One of these tools is BigQuery ML, which enables a user to develop and train ML models on large datasets within few minutes!
If you are not familiar with it already, BigQuery is a serverless data warehouse that enables SQL queries where you only pay for query-data-usage and storage (It is “similar” to Redshift on AWS). Since mid 2018, BigQuery has enabled users to build ML models with few lines of SQL code within few minutes. This post will walk you through the steps needed to build such ML models.
Author: Nezar Assawiel