Quick Start

Obtaining Converted Models

After installing the package, get the converted models as a dict from the models variable:

from msdss_models_sklearn import models as sklearn_models

sklearn_models['sklearn.linear_model.LinearRegression']

msdss_models_sklearn.core.LinearRegression

For more details, see msdss_models_sklearn.core.get_sklearn_models().

Note

The extracted models can also be imported directly from the package if you do not require all the models in your API:

from msdss_models_sklearn import LinearRegression, DecisionTreeClassifier

selected_models = [LinearRegression, DecisionTreeClassifier]
selected_models

[msdss_models_sklearn.core.LinearRegression,
 msdss_models_sklearn.core.DecisionTreeClassifier]

Adding Converted Models to Models API

To add the converted scikit-learn models to the msdss-models-api, set the models argument to the imported models:

from msdss_models_api import ModelsAPI
from msdss_models_sklearn import models as sklearn_models

# Create app using env vars
app = ModelsAPI(models=sklearn_models)

# Get the redis background worker to run using celery
worker = app.get_worker()

See msdss-models-api Quick Start for more details on running the API.

Note

Ensure that msdss-models-api has been installed and setup properly for the API to work.

See msdss-models-api Install.