Difference between revisions of "BiqQuery ML (BQML)"
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| − | BigQuery ML enables users to create and execute machine learning models in BigQuery using standard SQL queries. BigQuery ML democratizes machine learning by enabling SQL practitioners to build models using existing SQL tools and skills. BigQuery ML increases development speed by eliminating the need to move data. | + | BigQuery ML enables users to create and execute machine learning models in BigQuery using standard SQL queries. BigQuery ML democratizes machine learning by enabling SQL practitioners to build models using existing SQL tools and skills. BigQuery ML increases [[development]] speed by eliminating the need to move data. |
[http://cloud.google.com/bigquery/docs/bigqueryml BigQuery ML - Google] | [http://cloud.google.com/bigquery/docs/bigqueryml BigQuery ML - Google] | ||
Revision as of 13:36, 17 March 2023
YouTube search... ...Google search
- Platforms: AI/Machine Learning as a Service (AIaaS/MLaaS)
- Colab Getting Started with BigQuery ML
- Quickstart using the web UI in the GCP Console; to complete tasks like running queries, loading data, and exporting data. This quickstart shows you how to query tables in a public dataset and how to load sample data into BigQuery using the GCP Console.
- BigQuery Public Datasets | Google
BigQuery ML enables users to create and execute machine learning models in BigQuery using standard SQL queries. BigQuery ML democratizes machine learning by enabling SQL practitioners to build models using existing SQL tools and skills. BigQuery ML increases development speed by eliminating the need to move data.
BigQuery ML - Google
BiqQuery ML consists of a set of extensions of the SQL language that allows to create machine learning models, evaluate their predictive performance and make predictions for new data directly in BigQuery. Introduction to BigQuery ML | Pol Ferrando - Towards Data Science
