# BigQuery ML {% hint style="success" %} For this templates, you will need to install the [**BigQuery ML extension package**](https://docs.carto.com/carto-user-manual/workflows/components/bigquery-ml). {% endhint %} ### Create a classification model

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This example shows how to create a pipeline to train a classification model using [BigQuery ML](https://cloud.google.com/bigquery/docs/e2e-journey), evaluate the model and use it for prediction. In particular, we will create a classification model to estimate customer churn for a telecom company in California. This example workflow will help you see how telco companies can detect high-risk customers, uncover the reasons behind customer departures, and develop targeted strategies to boost retention and satisfaction by training a classification model. [**Download example**](https://storage.googleapis.com/carto-workflows-examples/files/bq_ml_create_classification_model.sql)

### Create a regression model

CARTO DW	BigQuery	Snowflake	Redshift	PostgreSQL	CARTO DW
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This example shows how to create a pipeline to train a regression model using [BigQuery ML](https://cloud.google.com/bigquery/docs/e2e-journey), evaluate the model and use it for prediction. In particular, we will create a regression model to predict the average network speed in the LA area. This example workflow will help you see how telco companies can improve network planning use by training a regression model to estimate the network speed in areas where no measurements are available. [**Download example**](https://storage.googleapis.com/carto-workflows-examples/files/bq_ml_create_regression_model.sql)

### Forecast

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This template shows how to create a forecast model using the BigQuery ML extension package for Workflows. There are three main stages involved: * **Training a model**, using some input data and adjusting to the desired parameters, * **Evaluating and understanding** the model and its performance, * **Predicting to a given horizon** and saving the results. [**Download example**](https://storage.googleapis.com/carto-workflows-examples/files/bq_ml_forecast.sql)

### Import a model

CARTO DW	BigQuery	Snowflake	Redshift	PostgreSQL	CARTO DW
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This example shows how to create a pipeline to import a pre-trained model using [BigQuery ML](https://cloud.google.com/bigquery/docs/reference/standard-sql/bigqueryml-syntax-create-onnx) and use it for prediction. In particular, we will import a regression model to predict the ration of crime counts per 1000 population in the Chicago area. [**Download example**](https://storage.googleapis.com/carto-workflows-examples/files/bq_ml_import.sql)

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