Advanced Predictive Modeling: Mastering Ensembles and Metamodeling
With Keith McCormick
Liked by 414 users
Duration: 1h 10m
Skill level: Advanced
Released: 4/4/2019
Course details
Ensembles involve groups of models working together to make more accurate predictions. When creating complete deployed solutions, data scientists may also leverage passing data from one model to another or using models in combination—also known as metamodeling. These techniques are dominant among winners of modeling competitions like Kaggle as well as leading data science teams around the world. In this advanced course, you can learn how to add ensembles and metamodeling to your toolset. Instructor Keith McCormick provides a conceptual introduction that can be applied in any program: R, Python, SPSS, or SAS. He introduces the most essential ensemble algorithms and explains the basics of metamodeling. Plus, review two case studies that show how to combine supervised and unsupervised ensembles and how to route subpopulations of data to different models in a metamodeling scenario.
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Meet the instructor
Learner reviews
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Bilal Khan, CFA
Bilal Khan, CFA
Risk & Analytics at CURO | Strategy | Advisory | Digital Transformation | Fintech | Data Science | Machine Learning
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Contents
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- Practice while you learn 1 exercise file
- Learn on the go Access on tablet and phone
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