Hands-On Tutorial: Leverage SAP HANA Machine Learning in the Cloud through the Predictive Analysis Library
The hard truth is that many machine learning projects fail to get set into production. It takes time and real effort to move from a machine learning model to a real business application. This is due to many different reasons for example:
- Limited data access
- Poor data quality
- Small computing power
- No version control
Of course, we can’t save the world with just one Hands-On tutorial, but we can at least try to make the life of a data scientist a little easier. In this blog post we will tackle these challenges by bringing the opensource world and SAP world together. In a nutshell, there will be no movement of training data from SAP HANA Cloud to our Python environment.
In order to "run" the provided sample codes, a SAP HANA database environment is required with the AFL-component installed, which includes the Predictive Analysis Library (PAL). Specific sample files will specify additional requirements if required.
The sample files can be downloaded and used within the respective user / developer environment, e.g. Python files may be opened and used within Jupyter Notebooks. The sample files don't require a install step for themselves, they are simply downloaded and then opened in the respective editor.
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Copyright (c) 2021 SAP SE or an SAP affiliate company. All rights reserved. This project is licensed under the Apache Software License, version 2.0 except as noted otherwise in the LICENSE file.