Machine Learning with R: A Hands-on Introduction from Robert Muenchen at Machine Learning Week, Las Vegas

[This article was first published on, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Join Robert Muenchen’s workshop about Machine Learning with R at Machine Learning Week on May 31 – June 4, 2020 in Las Vegas! 

Workshop Description 
The Workshop will take place in May 31, 2020. 

R offers a wide variety of machine learning (ML) functions, each of which works in a slightly different way. This one-day, hands-on workshop starts with ML basics and takes you step-by-step through increasingly complex modeling styles. This workshop makes ML modeling easier through the use of packages that standardize the way the various functions work. When finished, you should be able to use R to apply the most popular and effective machine learning models to make predictions and assess the likely accuracy of those predictions.

The instructor will guide attendees on hands-on execution with R, covering:
    • A brief introduction to R’s tidyverse functions, including a comparison of the caret and parsnip packages
    • Pre-processing data
    • Selecting variables
    • Partitioning data for model development and validation
    • Setting model training controls
    • Developing predictive models using naïve Bayes, classification and regression trees, random forests, gradient boosting machines, and neural networks (more, if time permits)
    • Evaluating model effectiveness using measures of accuracy and visualization
    • Interpreting what “black-box” models are doing internally
Hardware: Bring Your Own Laptop
Each workshop participant is required to bring their laptop. Software installation instructions are available at Attendees receive an electronic copy of the course materials and related R code after the workshop.

See more information about the workshop here.

To leave a comment for the author, please follow the link and comment on their blog: offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)