EARL Presentation on HR Analytics: Using ML to Predict Employee Turnover

Written by Matt Dancho on November 6, 2017





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The EARL Boston 2017 conference was held November 1 - 3 in Boston, Mass. There were some excellent presentations illustrating how R is being embraced in enterprises, especially in the financial and pharmaceutical industries. Matt Dancho, founder of Business Science, presented on using machine learning to predict and explain employee turnover, a hot topic in HR! We’ve uploaded the HR Analytics presentation to YouTube. Check out the presentation, and don’t forget to follow us on social media to stay up on the latest Business Science news, events and information!

EARL Boston 2017 Presentation

If you’re interested in HR Analytics and R applications in business, check out our 30 minute presentation from EARL Boston 2017! We talk about:

  • HR Analytics: Using Machine Learning for Employee Turnover Prediction and Explanation
  • Using H2O for automated machine learning
  • Using LIME for feature importance of black-box (non-linear) models such as neural networks, ensembles, and random forests

The code for the tutorial can be found in our HR Analytics article.

Download Presentation and Code on GitHub

The slide deck and code from the EARL Boston 2017 presentation can be downloaded from the Business Science GitHub site.

EARL 2017 Presentation

Download the EARL Boston 2017 Presentation Slides!

About Business Science

Business Science specializes in “ROI-driven data science”. Our focus is machine learning and data science in business applications. We help businesses that seek to add this competitive advantage but may not have the resources currently to implement predictive analytics. Business Science works with clients primarily in small to medium size businesses, guiding these organizations in expanding predictive analytics while executing on ROI generating projects. Visit the Business Science website or contact us to learn more!

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Data Science for Business Curriculum

Business Science University is an educational platform that teaches how to apply data science to business. Our offering includes of a fully integrated, project-based 3-Course R-Track.


BSU R-Track Course Curriculum


Each course takes the student through their progression in a data science journey. Begin your journey with DS4B 101-R which teaches foundations using the tidyverse. Next, master machine learning for business with DS4B 201-R, where you learn H2O and many advanced R packages. Finish with DS4B 301-R where you learn to develop high-performing web applications using Shiny, a powerful framework for productionizing R code.

R-Track Curriculum Summary

Business Analysis with R (Beginner) - Data Science Foundations 7-Week course 12 tidyverse Packages 2 business projects
Data Science For Business with R (Intermediate/Advanced) - Machine Learning + Business Consulting 10-Week course H2O, LIME, recipes, and 10 more packages 1 end-to-end business project
Web Apps for Business with Shiny (Advanced) - Web Frameworks (Bootstrap, HTML/CSS) and Shiny 6-Week course Shiny, shinytest, shinyloadtest, profvis, and more! Take machine learning model into production

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