This document discusses using ARIMA models with BigQuery ML to analyze time series data. It provides an overview of time series data and ARIMA models, including how ARIMA models incorporate AR and MA components as well as differencing. It also demonstrates how to create an ARIMA prediction model and visualize results using BigQuery ML and Google Data Studio. The document concludes that ARIMA models in BigQuery ML can automatically select the optimal order for time series forecasting and that multi-variable time series are not yet supported.
本セッションでは、W&B Coursesの中でも最も人気の高いコースである"Effective MLOps: Model Development (日本語字幕版コース名: 効果的なMLOps: モデル開発)"をギュッと濃縮したダイジェスト版を日本語ハンズオンでお届けいたします。W&Bの基本的な使い方、ベースラインからの改良方法などをシンプルな画像のセグメンテーションタスクを通じて学ぶことができます。
https://wandb.connpass.com/event/295345/
This document discusses using ARIMA models with BigQuery ML to analyze time series data. It provides an overview of time series data and ARIMA models, including how ARIMA models incorporate AR and MA components as well as differencing. It also demonstrates how to create an ARIMA prediction model and visualize results using BigQuery ML and Google Data Studio. The document concludes that ARIMA models in BigQuery ML can automatically select the optimal order for time series forecasting and that multi-variable time series are not yet supported.
本セッションでは、W&B Coursesの中でも最も人気の高いコースである"Effective MLOps: Model Development (日本語字幕版コース名: 効果的なMLOps: モデル開発)"をギュッと濃縮したダイジェスト版を日本語ハンズオンでお届けいたします。W&Bの基本的な使い方、ベースラインからの改良方法などをシンプルな画像のセグメンテーションタスクを通じて学ぶことができます。
https://wandb.connpass.com/event/295345/
The document discusses Docker and microservices. It provides motivation for using microservices, including code bloat, increased costs of code changes, and the need for diversity and specialization. It then covers Docker basics like creating images and containers. It discusses how Docker can be used to implement microservices and addresses challenges like transactions across containers and logging. The document concludes that organizations also need to be "micro-ized".