October 29-November 2, 2017
New York
Delivering on the promise of data science

Max Kuhn Instructor:
Max Kuhn
Software Engineer,
RStudio

Workshop

Sunday, October 29, 2017 in New York
Full-day: 12:00 - 7:30pm

R for Machine Learning:
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 both hands-on familiarity with any programming language (other than R) and basic conceptual knowledge about predictive modeling is sufficient background and preparation to participate in this workshop.

The 2 1/2 hour "R Bootcamp" is recommended preparation for this workshop.


What prior attendees have exclaimed

Prior attendees - Max is ean excellent speakers!

Workshop Description

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 (machine learning) 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 the use of these machine learning methods: 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

Applied Predictive Modeling 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.


Price and Registration Info:

Schedule

  • Workshop starts at 9:00am
  • Morning Coffee Break at 10:30am - 11:00am
  • Lunch provided at 12:30 - 1:15pm
  • Afternoon Coffee Break at 2:30pm - 3:00pm
  • End of the Workshop: 4:30pm

Instructor

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.

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