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SAP Learning

Developing Classification Models with the Python Machine Learning Client for SAP HANA

via SAP Learning

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Overview

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In this enablement, you will explore how to apply the machine learning workflow. The steps from feature extraction to model evaluation are illustrated to ensure a comprehensive understanding of the process. The scenario presented in this learning journey focuses on preventing employee churn, a key business problem addressed using SAP HANA Cloud Machine Learning. 

Syllabus

  • Understanding Classification with SAP HANA
    • Providing an Overview of Classification Models
    • Exploring the Demo Scenario - Preventing Employee Churn
    • Understanding Classification with SAP HANA
  • Setting Up the Environment and Analyzing Data with the SAP HANA Dataframes
    • Configuring the Python Machine Learning Client for SAP HANA
    • Exploring and Manipulating Data with SAP HANA DataFrames
    • Setting Up the Environment and Analyzing Data with the SAP HANA Dataframes
  • Training a PAL Classification Model for the Employee Churn dataset
    • Handling Data for Model Training
    • Training the Classification Model
    • Training a PAL Classification Model for the Employee Churn dataset
  • Evaluating and Testing the Model
    • Evaluating Model Performance
    • Generalizing the Model Using Test Data
    • Evaluating and Testing the Model

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