Skip to content

Scenario storyline: Predict the number of first class seats occupied in a flight using HANA ML - APL

Overview

In this exercise, our focus is on utilizing the SAP HANA Machine Learning (ML) algorithm to predict the occupancy of first-class seats on flights using APL Library.

To execute this exercise, we will leverage the Intelligent Scenario Lifecycle Management (ISLM) framework. ISLM serves as the foundation for creating and managing ML use cases seamlessly within the SAP S/4HANA stack.

This exercise includes the following steps:

  1. Creating a New Intelligent Scenario: We will begin by creating a new intelligent scenario that will encompass the predictive model for first-class seat occupancy.
  2. Operating the Intelligent Scenario: Once the scenario is set up, we will operate it to enable the prediction process.
  3. Visualizing Model Version Predictions: This step involves visualizing the predictions generated by the model versions within the intelligent scenario.
  4. Schedule Training: This step involves scheduling training for intelligent scenario based on selected frequency.

By the end of this exercise, participants will have gained hands-on experience in utilizing the ISLM framework and SAP HANA ML algorithm to enhance decision-making processes and improve customer experiences.