Predict Visitor Purchases with a Classification Model in BQML




Create a new dataset

Create a model and specify model options

Evaluate classification model performance

Improve model performance with Feature Engineering(Create second model)

Improve model performance with Feature Engineering(Better predictive power)

Predict which new visitors will come back and purchase

Predict Visitor Purchases with a Classification Model in BQML

1 jam 15 menit 7 Kredit


Google Cloud Self-Paced Labs


BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.

BigQuery Machine Learning (BQML, product in beta) is a new feature in BigQuery where data analysts can create, train, evaluate, and predict with machine learning models with minimal coding.

There is a newly available ecommerce dataset that has millions of Google Analytics records for the Google Merchandise Store loaded into BigQuery. In this lab you will use this data to run some typical queries that businesses would want to know about their customers' purchasing habits.


In this lab, you learn to perform the following tasks:

  • Use BigQuery to find public datasets

  • Query and explore the ecommerce dataset

  • Create a training and evaluation dataset to be used for batch prediction

  • Create a classification (logistic regression) model in BQML

  • Evaluate the performance of your machine learning model

  • Predict and rank the probability that a visitor will make a purchase

Bergabunglah dengan Qwiklabs untuk membaca tentang lab ini selengkapnya... beserta informasi lainnya!

  • Dapatkan akses sementara ke Google Cloud Console.
  • Lebih dari 200 lab mulai dari tingkat pemula hingga lanjutan.
  • Berdurasi singkat, jadi Anda dapat belajar dengan santai.
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