Predictive modeling with R

Abstract: 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

Bio: 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 (http://quantup.pl), 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.

Open Data Science Conference