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NCAA® March Madness®: Bracketology with Google Cloud

date_range 3시간 show_chart Fundamental universal_currency_alt 크레딧 11개

In this series of labs you will learn how to use BigQuery to analyze NCAA basketball data with SQL. Build a Machine Learning Model to predict the outcomes of NCAA March Madness basketball tournament games.

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  • 실습

    Using BigQuery in the Google Cloud Console

    This lab shows you how to query public tables and load sample data into BigQuery using the GCP Console. Watch the following short video Get Meaningful Insights with Google BigQuery.

    실습

    BigQuery: Qwik Start - Command Line

    This hands-on lab shows you how to query public tables and load sample data into BigQuery using the Command Line Interface. Watch the short videos Get Meaningful Insights with Google BigQuery and BigQuery: Qwik Start - Qwiklabs Preview.

  • 실습

    BigQuery 및 Cloud SQL용 SQL 소개

    이 실습에서는 기본적인 SQL 절을 학습하고 BigQuery 및 Cloud SQL에서 구조화된 쿼리를 실행하는 연습을 진행합니다.

  • 실습

    Exploring NCAA Data with BigQuery

    Use BigQuery to explore the NCAA dataset of basketball games, teams, and players. The data covers plays from 2009 and scores from 1996. Watch How the NCAA is using Google Cloud to tap into decades of sports data.

  • 실습

    Google 머신러닝을 사용한 브라켓톨로지

    이 실습에서는 머신러닝(ML)을 사용하여 공개 NCAA 데이터세트를 분석하고 NCAA 토너먼트 브라켓(대진표)을 예측합니다.

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