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

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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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