TechBytes: Using Python with Vantage | 3. Analytic Functions Modeling and Model Cataloging

Are you a Data Scientist who loves using Python and Jupyter Notebook but is having difficulty building performant analytics and machine-learning at scale? Don't despair - Teradata Vantage and Teradata Package for Python (teradataml) are here to help. They enable performant execution of complex analytics on large datasets, while using your favorite data science tools and language.  

In this third episode of the Using Python with Vantage TechBytes series, Alexander Kolovos demonstrates how to utilize teradataml to run Vantage in-database machine learning / modeling functions (XGBoost, Decision Forest, Confusion Matrix) as well as Model Cataloging feature.

Download Jupyter notebook used in the demonstration from a Teradata GitHub site:

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