Teradata Package for Python Function Reference on VantageCloud Lake - deploy - Teradata Package for Python - Look here for syntax, methods and examples for the functions included in the Teradata Package for Python.
Teradata® Package for Python Function Reference on VantageCloud Lake
- Deployment
- VantageCloud
- Edition
- Lake
- Product
- Teradata Package for Python
- Release Number
- 20.00.00.03
- Published
- December 2024
- ft:locale
- en-US
- ft:lastEdition
- 2024-12-19
- dita:id
- TeradataPython_FxRef_Lake_2000
- Product Category
- Teradata Vantage
- teradataml.opensource.sklearn._sklearn_wrapper._OpenSourceObjectWrapper.deploy = deploy(self, model_name, replace_if_exists=False)
- DESCRIPTION:
Deploys the model held by interface object to Vantage.
PARAMETERS:
model_name:
Required Argument.
Specifies the unique name of the model to be deployed.
Types: str
replace_if_exists:
Optional Argument.
Specifies whether to replace the model if a model with the same name already
exists in Vantage. If this argument is set to False and a model with the same
name already exists, then the function raises an exception.
Default Value: False
Types: bool
RETURNS:
The opensource object wrapper.
RAISES:
TeradataMLException if model with "model_name" already exists and the argument
"replace_if_exists" is set to False.
EXAMPLES:
>>> from teradataml import td_sklearn
>>> model = td_sklearn.LinearRegression(normalize=True)
>>> model
LinearRegression(normalize=True)
# Example 1: Deploy the model held by interface object to Vantage.
>>> lin_reg = model.deploy("linreg_model_ver_2")
Model is saved.
>>> lin_reg
LinearRegression(normalize=True)
# Example 2: Deploy the model held by interface object to Vantage with the name same
# as that of model that already existed in Vantage.
>>> lin_reg = model.deploy("linreg_model_ver_2", replace_if_exists=True)
Model is deleted.
Model is saved.
>>> lin_reg
LinearRegression(normalize=True)