Machine Learning at Indeed: Scaling Decision Trees

This talk was held on Wednesday, February 26, 2014.

Decision trees are a widely used machine learning technique for supervised classification. Indeed’s data sets consist of tens of billions of documents with millions of distinct features. Since decision trees back some of our most important features, we built a custom distributed system to efficiently train them. We build dozens of decision trees across this data every day. This same system now powers our internal analytical tools that enable quick data-driven decision-making at Indeed.

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Speaker

Andrew Hudson is Indeed’s CTO.

Originally published at Indeed Engineering Blog.