From the course: Google Cloud Digital Cloud Leader Cert Prep: 3 Innovating with Google Cloud Artificial Intelligence
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BigQuery ML - Google Cloud Platform Tutorial
From the course: Google Cloud Digital Cloud Leader Cert Prep: 3 Innovating with Google Cloud Artificial Intelligence
BigQuery ML
- [Instructor] Machine learning on large data sets requires extensive programming and knowledge of ML frameworks. These requirements restrict solution development to a very small set of people within each company, and they exclude data analysts who understand the data but have limited machine learning knowledge and programming expertise. Although BigQuery started solely as a data warehouse, over time, it has evolved to provide additional features that support the data to AI lifecycle. BigQuery ML democratizes the use of machine learning by empowering data analysts, the primary data warehouse users to build and run models by using existing business intelligence tools and spreadsheets. Predictive analytics can guide business decision making across the organization. Using Python or Java to program an ML solution isn't necessary. Models are trained and accessed directly in BigQuery by using SQL, which is a language familiar to data analysts. BigQuery ML brings machine learning to the…
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