Monday, May 15, 2017 in San Francisco
Full-day: 12:00 - 7:30pm
R for Predictive Modeling:
A Hands-On Introduction
Intended Audience: Practitioners who wish to learn how to execute on predictive analytics by way of the R language; anyone who wants "to turn ideas into software, quickly and faithfully."
Knowledge Level: Either hands-on experience with predictive modeling (without R) or hands-on familiarity with any programming language (other than R) is sufficient background and preparation to participate in this workshop.
The three-hour "R Bootcamp" is recommended preparation for this workshop.
This one-day session provides a hands-on introduction to R, the well-known open-source platform for data analysis. Real examples are employed in order to methodically expose attendees to best practices driving R and its rich set of predictive modeling packages, providing hands-on experience and know-how. R is compared to other data analysis platforms, and common pitfalls in using R are addressed.
The instructor, a leading R developer and the creator of CARET, a core R package that streamlines the process for creating predictive models, will guide attendees on hands-on execution with R, covering:
- A working knowledge of the R system
- The strengths and limitations of the R language
- Preparing data with R, including splitting, resampling and variable creation
- Developing predictive models with R, including decision trees, support vector machines and ensemble methods
- Visualization: Exploratory Data Analysis (EDA), and tools that persuade
- Evaluating predictive models, including viewing lift curves, variable importance and avoiding overfitting
Each participant will receive a copy of Max's book Applied Predictive Modeling.
Hardware: Bring Your Own Laptop
Each workshop participant is required to bring their own laptop running Windows or OS X. The software used during this training program, R, is free and readily available for download.
Attendees receive an electronic copy of the course materials and related R code at the conclusion of the workshop.
- Lunch provided at 12:00pm
- Workshop starts at 12:30pm
- Afternoon Coffee Break at 2:30 - 3:00pm
- Afternoon Coffee Break at 5:30pm - 6:00pm
- End of the Workshop: 7:30pm
Max Kuhn, Software Engineer, RStudio
Max Kuhn is a software engineer at RStudio, a leading company for R software and tools. He is currently working on improving R's modeling capabilities. He has a Ph.D. in Biostatistics.
Max was a Director of Nonclinical Statistics at Pfizer Global R&D in Connecticut. He was applying models in the pharmaceutical and diagnostic industries for over 18 years.
Max is the author of eight R packages for techniques in machine learning and reproducible research and is an Associate Editor for the Journal of Statistical Software. He, and Kjell Johnson, wrote the book Applied Predictive Modeling, which won the Ziegel award from the American Statistical Association, which recognizes the best book reviewed in Technometrics in 2015.
He has taught courses on modeling, including many classes for Predictive Analytics World, the useR! conference, the Open Data Science Conference, the India Ministry of Information Technology, and others.