tdapiclient Python library allows AWS SageMaker and Teradata users to use AWS SageMaker Python library's interface to train/predict using teradataml DataFrame. tdapiclient will transparently convert teradataml DataFrame in S3 address to be used for training and it will also allow user to use teradataml DataFrame as input for inference.
tdapiclient also allows Azure-ML and Teradata Users to use easier interface to train/predict using teradataml DataFrame. tdapiclient will transparently convert teradataml DataFrame to azure-ml dataset or blob store to be used for training and it will allow users to use teradataml DataFrame as input for inference. Additionally , tdapiclient also allows to deploy azure-ml trained models in Teradata Vantage system for in-database scoring using BYOM functionality.
Teradata recommends downloading tdapiclient library from PyPi location : https://pypi.org/project/tdapiclient/.
Download from downloads.teradata.com location if your organization does not allow you to install directly from https://pypi.org/project/tdapiclient/.
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