From the course: Data Warehousing on Google Cloud Platform
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Introduction to BigQuery ML - Google Cloud Platform Tutorial
From the course: Data Warehousing on Google Cloud Platform
Introduction to BigQuery ML
- [Instructor] BigQuery ML allows data-science and analytics teams to create machine-learning models. BigQuery ML supports several different models, as well as externally-trained or important models. Let's take a look at how you can create a machine-learning model right within SQL. It's accessible through the web console, command line tools, Google Collab, and Jupyter Notebooks. What's really cool about BigQuery ML is that it makes creating machine-learning models more accessible. For example, as developers and analysts that are familiar with SQL Code language, we can build models within SQL without having to learn Python or Java. We can access the data within our data warehouse to train our models and use the same platform without having to learn about other tools. We can also use prebuilt remote models against our BigQuery data, including large language models like generative ai, and incorporate document processing and audio transcription into your BigQuery workflow. Let's take a…
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