Site icon R-bloggers

Webinar and free e-book on data preparation with R

[This article was first published on Revolutions, 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.

Just a quick heads up that Nina Zumel, co-founder and principal consultant at Win-Vector LLC will be presenting a webinar at 10AM Pacific Time on Thursday March 17, Data Preparation Techniques with R. Nina is the co-author of Practical Data Science with R and blogs frequently at the Win-Vector blog (and contributes the occasional guest blog here), and has a wealth of experience managing data in R as a consultant. This webinar will be a great opportunity to learn tips and tricks from Nina on the best way to handle real-world data sets in R.

I'll be hosting the webinar and delivering your questions to Nina live during the event. If you can't join live, you'll receive an email afetr the event with a link to the slides and replay. All registrants will also receive a free copy of the new e-book Preparing Data for Analysis with R by our presenter, Nina Zumel.

Data quality is the single most important item to the success of your data science project. Preparing data for analysis is one of the most important, laborious and yet, neglected aspects of data science. Many of the routine steps can be automated in a principled manner. This webinar will lay out the statistical fundamentals of preparing data. Our speaker, Nina Zumel, principal consultant and co-founder of Win-Vector, LLC, will cover what goes wrong with data and how you can detect the problems and fix them.

To register for the webinar and receive your free e-book, follow the link below.

Microsoft Advanced Analytics and IoT: Data Preparation Techniques with R

To leave a comment for the author, please follow the link and comment on their blog: Revolutions.

R-bloggers.com 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.