How to build and deploy a demand forecasting solution with BigQuery ML

From the creator

Learn how to use BigQuery ML to train and deploy a demand forecasting solution. With potentially millions of products, for a data science and engineering team to create multi-millions of forecasts is one thing, but to procure and manage the infrastructure to handle an end-to-end model training and forecasting solution, this can quickly become overwhelming, especially for large businesses. This is a step-by-step video that explores the demand forecasting pattern in the Notebook linked below and helps walk you through the entire process of building such a system in your organization. You will learn how to: •Prepare the training data in BigQuery •Train and evaluate a time-series model with BigQuery ML •Visualize the forecasts in a dashboard •Schedule and automate model retraining Solutions guide → http://goo.gle/3om3dcz Notebook here → http://goo.gle/39kf9Hc More Smart Analytics Reference Patterns → http://goo.gle/3sZnU1m Subscribe to Google Developers → https://goo.gle/developers

Published 2021-01-27 · Watch on YouTube ↗
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