IBM 0A039G - Advanced Machine Learning Models Using IBM SPSS Modeler (V18.2)
Seminar
In Hamburg
Beschreibung
-
Kursart
Seminar
-
Ort
Hamburg
-
Beginn
auf Anfrage
Knowledge of your business requirementsRequired: 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.
Standorte und Zeitplan
Lage
Beginn
Beginn
Hinweise zu diesem Kurs
Data scientistsBusiness analystsExperienced users of IBM SPSS Modeler who want to learn about advanced techniques in the software
Meinungen
Erfolge dieses Bildungszentrums
Sämtlich Kurse sind auf dem neuesten Stand
Die Durchschnittsbewertung liegt über 3,7
Mehr als 50 Meinungen in den letzten 12 Monaten
Dieses Bildungszentrum ist seit 15 Mitglied auf Emagister
Themen
- .net
- Basic
- Modeling
- SPSS
- IBM
Inhalte
Introduction to advanced machine learning models • Taxonomy of models • Overview of supervised models • Overview of models to create natural groupings
Group fields: Factor Analysis and Principal Component Analysis • Factor Analysis basics • Principal Components basics • Assumptions of Factor Analysis • Key issues in Factor Analysis • Improve the interpretability • Factor and component scores
Predict targets with Nearest Neighbor Analysis • Nearest Neighbor Analysis basics • Key issues in Nearest Neighbor Analysis • Assess model fit
Explore advanced supervised models • Support Vector Machines basics • Random Trees basics • XGBoost basics
Introduction to Generalized Linear Models • Generalized Linear Models • Available distributions • Available link functions
Combine supervised models • Combine models with the Ensemble node • Identify ensemble methods for categorical targets • Identify ensemble methods for flag targets • Identify ensemble methods for continuous targets • Meta-level modeling
Use external machine learning models • IBM SPSS Modeler Extension nodes • Use external machine learning programs in IBM SPSS Modeler
Analyze text data • Text Mining and Data Science • Text Mining applications • Modeling with text data
IBM 0A039G - Advanced Machine Learning Models Using IBM SPSS Modeler (V18.2)