Applying BQML's Classification, Regression, and Demand Forecasting for Retail Applications

Advanced 5단계 5시간 크레딧 25개

In this quest you will learn how to use several BQML features to improve retail use cases. Predict the demand for bike rentals in NYC with demand forecasting, leverage regression to estimate the time it will take for a ticket to be solved with the help of an automated agent developed using Dialogflow, and see how to use BQML for a classification task that predicts the likelihood of a website visitor making a purchase.

Quest Outline


BigQuery 및 Cloud SQL용 SQL 소개

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

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Implement a Helpdesk Chatbot with Dialogflow & BigQuery ML

In this lab you will train a simple machine learning model for predicting helpdesk response time using BigQuery Machine Learning.

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Building Demand Forecasting with BigQuery ML

In this lab you will build a time series model to forcast demand of multiple products using BigQuery ML. This lab is based on a blog post and featured in an episode of Cloud OnAir.


Predict Visitor Purchases with a Classification Model in BQML

In this lab you will use a newly available ecommerce dataset to run some typical queries that businesses would want to know about their customers’ purchasing habits.

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BigQuery ML 예측 모델을 사용하여 택시 요금 예측하기

이 실습에서는 BigQuery 공개 데이터세트에서 제공되는 수백만 건의 뉴욕 옐로캡 택시 운행 데이터를 살펴보고, BigQuery 내에서 ML 모델을 생성하여 요금을 예측하며, 이러한 예측을 수행하는 모델의 성능을 평가해봅니다.

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