Bracketology with Google Machine Learning |
Автор: Shabnam Hamidi
Загружено: 2025-05-11
Просмотров: 133
BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without managing infrastructure or needing a database administrator. BigQuery uses SQL and takes advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.
BigQuery ML allows data analysts to use their SQL knowledge to build machine learning models quickly right where their data already lives in BigQuery.
In BigQuery, there is a publicly available dataset for NCAA basketball games, teams, and players. The game data covers play-by-play and box scores back to 2009, as well as final scores back to 1996. Additional data about wins and losses goes back to the 1894-5 season in some teams' cases.
In this lab, you use BigQuery ML to prototype, train, evaluate, and predict the 'winners' and 'losers' between two NCAA basketball tournament teams.
Lab Link:
https://www.cloudskillsboost.google/p...
Code Link:
https://github.com/shbnm93/Bracketolo...
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