Advanced Machine Learning Models Using IBM SPSS Modeler V18.2...
- CMDBID 75714
- Course Code 0A039G
- Duration 1 Days
IBM Analytics DS&BA SPSS Course
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Overview
Advanced Machine Learning Models Using IBM SPSS Modeler V18.2 0A039Gis a practical training course for teams that need structured, instructor-led skills in Advanced Machine Learning Models, Using IBM SPSS Modeler, V18.2. CourseMonster has rewritten this summary to make the page clearer for learners, managers and search engines while preserving the key learning outcomes.
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.
. Explore more IBM traininghereUseful links: IBM Training | Data and Analytics training at CourseMonster | CourseMonster course page
CourseMonster SEO course note: Advanced Machine Learning Models Using IBM SPSS Modeler V18.2 0A039G Training Course | CourseMonster has been positioned as a practical IBM learning pathway for teams that need searchable, role-based training outcomes rather than a generic course description. The page now highlights Machine, Learning, Models, IBM, SPSS, certification readiness, workplace application and visible next-step links so learners can compare this course with related CourseMonster programmes.The course is listed as 1 day(s), making it suitable for structured team scheduling.It is especially relevant for data scientists business analysts experienced users of ibm spss modeler who want to learn about advanced techniques in the software
Related CourseMonster courses: Introduction to Machine Learning Models Using IBM SPSS Modeler V18.2 0A079G Training Cours | Creating, Testing, and Deploying Machine Learning Models with IBM Watson Studio V4.8 W7L54 | IBM SPSS Modeler Foundations V18.2 0A069G Training Course | CourseMonster
Browse the vendor/category pathway: IBM training courses on CourseMonster
Audience
- Data scientists
- Business analysts
- Experienced users of IBM SPSS Modeler who want to learn about advanced techniques in the software
Skills Gained
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
Useful links: IBM Training | Data and Analytics training at CourseMonster | CourseMonster course page
Additional workplace outcomes: Participants can explain where Advanced Machine Learning Models Using IBM SPSS Modeler V18.2 0A039G Training Course | CourseMonster fits in a wider IBM skills roadmap, identify related certifications or follow-on courses, and apply the concepts to real project, operations or service delivery scenarios.
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.
Outline
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
. Explore more IBM traininghereUseful links: IBM Training | Data and Analytics training at CourseMonster | CourseMonster course page
Suggested learning path: After this course, compare related options via the links in the overview and the IBM training category.
Certification
Exam and certification details
This course may support a vendor exam, digital badge or professional certification depending on the selected delivery option. Delegates should confirm exam inclusion, voucher availability, prerequisites, pass mark and version before booking.
Official vendor training information: IBM Training.
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