ABOUT THIS BOOK
Machine Learning is a critical tool used for gaining actionable insight, more accurate foresight, and relevant inferences into your ever-increasing amount of data. A widespread application of machine learning is the recommendation engine. Apache Mahout, a project to build scalable machine learning libraries, greatly simplifies the process of extracting recommendations and relationships from datasets.
In this guide, Practical Machine Learning: Innovations in Recommendation, authors and Mahout committers Ted Dunning and Ellen Friedman, shed light on a more approachable recommendation engine design and the business advantages for leveraging this innovative implementation style.
Download this latest guide from O’Reilly to learn:
- A simplified approach for building effective recommender systems
- Innovative use of search technology to deploy a recommendation engine at scale
- Tips and tricks to ingest data in real-time and improve recommenders
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