Advanced Machine Learning Models Using IBM SPSS Modeler (V18.2) (0A039G)

 

Who should attend

  • Data scientists
  • Business analysts
  • Experienced users of IBM SPSS Modeler who want to learn about advanced techniques in the software

Prerequisites

  • Knowledge of your business requirements
  • Required: IBM SPSS Modeler Foundations (V18.2) course (0A069G/0E069G) or equivalent knowledge of how to import, explore, and prepare data with IBM SPSS Modeler v18.2, and know the basics of modeling.
  • Recommended: Introduction to Machine Learning Models Using IBM SPSS Modeler (V18.2) course (0A079G/0E079G), or equivalent knowledge or experience with the product about supervised machine learning models (CHAID, C&R Tree, Regression, Random Trees, Neural Net, XGBoost), unsupervised machine learning models (TwoStep Cluster), and association machine learning models such as APriori.

Course Content

This course presents advanced models available in IBM SPSS Modeler. The participant is first introduced to a technique named PCA/Factor, to reduce the number of fields to a number of core factors, referred to as components or factors. The next topics focus on supervised models, including Support Vector Machines, Random Trees, and XGBoost. Methods are reviewed on how to analyze text data, combine individual models into a single model, and how to enhance the power of IBM SPSS Modeler by adding external models, developed in Python or R, to the Modeling palette.

Precios & Delivery methods

Entrenamiento en línea

Duración 1 día

Precio
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Classroom training

Duración 1 día

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Instructor-led Online Training:   Este es un curso en línea Guiado por un Instructor

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Alemania

Entrenamiento en línea Zona Horaria: Europe/Berlin Este curso será presentado por un socio Inscripción
Entrenamiento en línea Zona Horaria: Europe/Berlin Lenguaje del curso: Inglés Este curso será presentado por un socio Inscripción
Entrenamiento en línea Zona Horaria: Europe/Berlin Este curso será presentado por un socio Inscripción