Build and operationalize
predictive models on relational data in no time

import getml.aggregations as aggregations
import getml.engine as engine
import getml.loss_functions as loss_functions
import getml.models as models
import getml.predictors as predictors

population_placeholder = models.Placeholder(
 name=“POPULATION”
)

peripheral_placeholder = models.Placeholder(
 name=“PERIPHERAL”
)

population_placeholder.join(peripheral_placeholder,
 “join_key”, “time_stamp”)

model = models.MultirelModel(
 aggregation=[aggregations.Count, aggregations.Sum],
 population=population_placeholder,
 peripheral=[peripheral_placeholder],
 predictor=predictors.XGBoostRegressor(),
 num_features=10
).send()

Build and operationalize predictive models on relational data in no time

Getting started tutorial ->

Technical documentation ->