Machine Learning is an essential component of every major tech product today. With tools like BigQuery ML, you don't have to be a data scientist to quickly and easily incorporate ML into your applications.
At a recent C2C Deep Dive event hosted by the Google Cloud startups team, Google Cloud AI/ML Specialist Customer Engineers Mike Walker and Rob Vogelbacher explained how you can use BigQuery ML to power insights for you and your customers. There are many built-in algorithms for regression, classification, clustering, forecasting, and recommendations that you can train with just a few lines of SQL. All these help you learn more from your data in a short time and in a cost-effective way. The models you build can be called from BigQuery or from external applications.
The recording from this session includes the following topics:
- (0:00) Introduction from C2C
- (2:35) What is BigQuery?
- (6:00) Decoupled storage and compute on BigQuery
- (8:00) Typical ML Workflow
- (10:00) BigQuery ML and AI
- (11:30) BigQuery ML-supported models and features
- (17:30) BigQuery Use cases
- (18:30) BigQuery Explainable AI
- (21:05) AutoML Tables and BigQuery ML
- (23:25) BigQuery ML Example Models: Miami Housing Dataset
- (41:30) Audience Q&A
Watch the full recording of the conversation below:
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