Add AWS Sagemaker Endpoint deployment and model prediction using api-endpoint

Summary

This release provides creating an AWS Sagemaker endpoint and installing model specific UDF script enabling the user to include prediction via the deployed endpoint in its queries. In addition, this release also includes deletion of the created endpoint and associated resources.

Features

• #28: Added lua and python scripts for endpoint operations
• #22: Added PredictionUDF using api-endpoint

Add model training with AWS SageMaker Autopilot on data in Exasol and Status Job polling.

Summary

This is the initial release of the sagemaker-extension which trains Machine Learning Models on data stored in Exasol using AWS SageMaker Autopilot service. Furthermore, this release provides a command line tool to deploy the Lua and UDF scripts to the database. Please check out the user guide for the installation, deployment, and usage steps.

Features

• #4: Added initial project setup
• #6: Added documentation folder
• #1: Added Lua export scripts
• #2: Added UDF which trains Autopilot model
• #14 Added CREATE SCRIPT statements for deployment of the training UDF
• #13 Created Python CLI Tool to deploy the extension
• #17 Enhanced the deployment of the extension
• #11 Added UDF which polls Autopilot training status
• #3 Added user guide