EARL Presentation on HR Analytics: Using ML to Predict Employee Turnover
Written by Matt Dancho on November 6, 2017
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.
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!