Example: Deploy and Load Model Trained outside Vantage | teradataml OpenSourceML - Example: Deploy and Load Model Trained outside Vantage - Teradata Vantage

>>> import numpy as np

>>> from sklearn.pipeline import make_pipeline
>>> from sklearn.preprocessing import StandardScaler

>>> X = np.array([[-1, -1], [-2, -1], [1, 1], [2, 1]])
>>> y = np.array([1, 1, 2, 2])

>>> from sklearn.svm import SVC

>>> clf = make_pipeline(StandardScaler(), SVC(gamma='auto'))

>>> clf.fit(X, y)

Pipeline(steps=[('standardscaler', StandardScaler()),
                ('svc', SVC(gamma='auto'))])

# Import the module.
>>> from teradataml import td_sklearn as osml
>>> svc_obj = osml.deploy(model_name="svc_outside_tdml", model=clf, replace_if_exists=True)

Model is deleted.
Model is saved.

>>> loaded2 = osml.load(model_name="svc_outside_tdml")
>>> loaded2

Pipeline(steps=[('standardscaler', StandardScaler()),
                ('svc', SVC(gamma='auto'))])

>>> loaded2.predict(df_x_clasif.select(["col1", "col2"]))

             col1                 col2    pipeline_predict_1
0.426749100345748    0.052892805973648                     2
0.061358610926176    -0.32391973812397                     1
 1.06516942678559     1.37093616727654                     2
 1.34487963860504    0.006631689510300                     2
 1.13904878664119     1.05078416796634                     2
0.615820493677217    0.351753443920848                     2
-0.58236154328365    -0.95815122115123                     1
 1.36289521790798    0.273506135473117                     2
-1.24268158066154    -1.14715279214675                     1
0.790100366929475    0.685306235288764                     2