HR Analytics: Using Machine Learning to Predict Employee Turnover - Matt Dancho, Business Science

This presentation was recorded at #H2OWorld 2017 in Mountain View, CA.

Enjoy the slides: https://www.slideshare.net/0xdata/hr-analytics-using-machine-learning-to-predict-employee-turnover.

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In this talk, we discuss how we implemented H2O and LIME to predict and explain employee turnover on the IBM Watson HR Employee Attrition dataset. We use H2O’s new automated machine learning algorithm to improve on the accuracy of IBM Watson. We use LIME to produce feature importance and ultimately explain the black-box model produced by H2O.

Matt Dancho is the founder of Business Science (www.business-science.io), a consulting firm that assists organizations in applying data science to business applications. He is the creator of R packages tidyquant and timetk and has been working with data science for business and financial analysis since 2011. Matt holds master’s degrees in business and engineering, and has extensive experience in business intelligence, data mining, time series analysis, statistics and machine learning. Connect with Matt on twitter (https://twitter.com/mdancho84) and LinkedIn (https://www.linkedin.com/in/mattdancho/).

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