Associate Data Practitioner
Unlock the power of your data in the cloud! Get hands-on with Google Cloud's core data services like BigQuery and Looker to validate your practical skills in data ingestion, analysis, and management, and earn your Associate Data Practitioner certification!
Gauge your current knowledge
Gauge your current knowledge
2.3 Define, train, evaluate, and use ML models
Study Guides for Sub-Sections
BigQuery ML (BQML) is a powerful service on Google Cloud that allows data practitioners to create and execute Machine Learning models using standard SQL queries. B...
Model metadata management in Google Cloud’s Model Registry is essential for teams to track, version, and deploy machine learning models consistently. By storing metadata i...
BigQuery ML allows you to perform inference by utilizing models that you have already trained. In this context, inference means applying a model to new or existing dat...
BigQuery ML enables users to create and manage machine learning (ML) models directly within the Google Cloud Platform. This service is designed for data analysts a...
Setting up and managing datasets in Google Cloud Platform (GCP) is the first step in preparing for machine learning. Tools like Cloud Storage and BigQuery<...
To establish a remote connection to BigQuery for integrating large language models (LLMs), you must first understand how to configure secure connections. These con...