Drawing business conclusions

In this section, we'll formulate some final considerations using the results that we got from the application of our machine learning model.

Using the query executed in the Using the K-Means clustering model section, we can create a table that contains the Top Drivers identified by the clustering_by_speed_and_income K-Means machine learning model, as follows:

CREATE OR REPLACE TABLE `07_chicago_taxi_drivers.top_taxi_drivers_by_speed_and_income` AS
SELECT
  * EXCEPT(nearest_centroids_distance)
FROM
  ML.PREDICT( MODEL `07_chicago_taxi_drivers.clustering_by_speed_and_income`,
    (
      SELECT *
      FROM
        `07_chicago_taxi_drivers.taxi_speed_and_income`
    ))
WHERE CENTROID_ID=1; 

The execution of the query generates a top_taxi_drivers_by_speed_and_income table that contains...