GSP327 solutions

1) 
```
 CREATE OR REPLACE TABLE taxirides.taxi_training_data (
  `pickup_datetime` TIMESTAMP, 
  `pickuplon` FLOAT64,
  `pickuplat` FLOAT64,
  `dropofflon` FLOAT64,
  `dropofflat` FLOAT64,
  `passengers` FLOAT64,
  `fare_amount` FLOAT64
 )

as (

Select
  pickup_datetime,
  pickup_longitude AS pickuplon,
  pickup_latitude AS pickuplat,
  dropoff_longitude AS dropofflon,
  dropoff_latitude AS dropofflat,
  passenger_count AS passengers,
  ( tolls_amount + fare_amount ) AS fare_amount
FROM
  `taxirides.historical_taxi_rides_raw`
WHERE
  trip_distance > 0
  AND fare_amount >= 2.5
  AND pickup_longitude > -75
  AND pickup_longitude < -73
  AND dropoff_longitude > -75
  AND dropoff_longitude < -73
  AND pickup_latitude > 40
  AND pickup_latitude < 42
  AND dropoff_latitude > 40
  AND dropoff_latitude < 42
  AND passenger_count > 0
  AND RAND() < 999999 / 1031673361
)

```
2)
```
CREATE or REPLACE MODEL taxirides.fare_model 
OPTIONS (model_type='linear_reg',
    labels=['fare_amount']
) 
AS
WITH taxitrips AS (
  SELECT
    *,
    ST_Distance(ST_GeogPoint(pickuplon, pickuplat), ST_GeogPoint(dropofflon, dropofflat)) AS euclidean
  FROM
    `taxirides.taxi_training_data` 
)
  SELECT
    *
  FROM
    taxitrips
```

3)
```
 CREATE OR REPLACE TABLE taxirides.2015_fare_amount_predictions 
 as (


        SELECT
          *
        FROM
          ML.PREDICT(MODEL `taxirides.fare_model`,
        (

        WITH taxitrips AS (
          SELECT
            *,
            ST_Distance(ST_GeogPoint(pickuplon, pickuplat), ST_GeogPoint(dropofflon, dropofflat)) AS euclidean
          FROM
            `taxirides.report_prediction_data` 
        )
          SELECT
            *
          FROM
            taxitrips
        )
        )

)

```