Predictive modeling with R
Predictive modeling with R


R is a standard tool for predictive modeling. It allows to use hundreds of predictive models and build really complex workflows.

The workshop is a guided tour through the most important R packages. It is illustrated with working R examples. You will learn how to use R for predictive modeling including feature selection, model building, validation, and deployment.

You will learn what is the correct process of predictive models building and how to:

- use R for predictive modeling including feature selection, model building, validation, and deployment
- work with an universal and powerful package `caret`
- a couple of specialized packages like `xgboost` and `caretEnsemble`
- supporting packages like `PMML`
- as a help we will use H2O


Artur has over twenty years of experience in deep business analytics, Data Science, and Machine Learning projects. He worked for various companies: from start-ups to international corporations, and in various roles: as an employee, a consultant, and a business owner. He spent over ten years working as a statistician in a commercial bank. At the same time he received Ph.D. in Mathematics and wrote several scientific papers. He currently runs his company QuantUp (, focusing on giving value to companies using Data Science, Machine Learning, software development and commercial trainings. He has led nearly one hundred of real-world Data Science projects and several thousand hours of commercial trainings in this field. A co-owner, Vice CEO and CSO of a Swedish bioinformatics company MedicWave. Artur has a long-time experience working with open source software and promotes its use in business applications during numerous conferences. He is a fan of the R language and a co-author of a book on forecasting in R.

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