Name: Reproducible Data Analysis with Revolution R Open
Start: 2015-01-29T18:00:00-06:00
End: 2015-01-29T21:00:00-06:00
Location: Enova International

David Smith from Revolution Analytics has moved to Chicago! We are very lucky to have him speaking about reproducible analysis with R, a very hot topic.

Doors open at 5:30. Talk begins at 6:00. Pizza provided by Revolution Analytics!

Here are David's abstract and bio:

Good data analysis is reproducible. If someone else can’t independently replicate your results from your data, the consequences can be severe. With R, a major challenge for reproducibility is the ever-changing package ecosystem: it's all too easy to develop an R script using packages, only to find collaborators will download later versions of those packages when they attempt to reproduce your results, and outcome can be unpredictable!

In this talk I'll introduce the Reproducible R Toolkit, and the "checkpoint" package, included with Revolution R Open, and describe some best practices for writing reliable, reproducible R code with packages.

Bio:
David Smith is Chief Community Officer at Revolution Analytics. With a background in data science, he writes daily about applications of R and predictive analytics at the Revolutions blog (blog.revolutionanalytics.com (http://blog.revolutionanalytics.com/)), and was named a top 10 influencer on the topic of “Big Data” by Forbes. Follow David on Twitter as @revodavid.

Paul Teetor

Chase Carpenter

The Chicago R User Group (CRUG)

Chicago R User Group

Technology

Programming in R

Software Development

Deep Learning

Computer Programming

Artificial Intelligence

Predictive Analytics

Machine Learning

Applied Statistics

Open Source

Data Analytics

R Project for Statistical Computing

Quantitative Finance

Data Science using R

Data Science using Python

Statistical Computing

Reproducible Data Analysis with Revolution R Open

Enova International

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The Chicago R User Group (CRUG)

Reproducible Data Analysis with Revolution R Open

The Chicago R User Group (CRUG)

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