Amazon SageMaker is a cloud machine learning platform which offers services to create, train and deploy machine learning models in the cloud. It also offers services to export models and use the models in other services.
- API_Request In-database Function
This in-database function enables Vantage users to connect with an AWS endpoint for analytic services using a Vantage query (SQL).
For example, with this function, users can score Vantage data using an Amazon SageMaker deployed model, with results returned as a query result set.
- Teradata Package for Python (teradataml) SageMaker Extension Library (tdapiclient)
This client package allows data scientists and developers to use their Python development environment to connect to Vantage and call the API_Request function with a Python-style function call instead of SQL, for scoring and inference of Vantage data with AWS endpoints.
API_Request In-database Function
Amazon SageMaker is a platform for data scientists to train and deploy machine learning models as a service on the Amazon cloud, accessible by address 'endpoints'. With the Teradata Vantage API_Request feature, Teradata customers can connect to these AWS endpoints through a query to do real-time scoring on data directly from Vantage.
- Data scientists leverage Vantage for data integration, data cleaning and feature engineering;
- Data scientists use data for training and model fitting with Amazon SageMaker or other AWS machine learning services;
- Data scientists deploy models to AWS endpoints;
- Business users then consume those analytic services with Vantage API_Request query, using endpoint and AWS authentication details.
For example, users can query Amazon SageMaker inference in real-time in their BI tools and dashboards using API_Request in-database function and API_Type as "aws-sagemaker".
Teradataml SageMaker Extension Library (tdapiclient)
The teradataml SageMaker Extension Library (tdapiclient) allows SageMaker and Teradata users to use the same Amazon SageMaker Python library interfaces to train and predict using data in Teradata Vantage tables.
tdapiclient transparently converts and copies the Teradata DataFrame to S3 for training; and for inference, it will use the data directly from Vantage input tables or queries.