In this session, we will introduce a Mahout, a machine learning library that has multiple algorithms implemented on top of Hadoop and HDInsight. We will start by introducing the foundational concepts needed to understand clustering, classification and collaborative filtering before demonstrating what it takes to get started with Mahout. In addition to learning how you get Mahout set-up, you will learn what it takes to process and prepare data, how to execute an “embarrassing parallel” batch recommendation job and subsequently how to integrate the result back into your existing ecosystem.
Christopher Price is a Senior Consultant with Microsoft, based in Tampa, FL. He has a bachelor's degree in MIS and an MBA, both from the University of South Florida, and previously worked as a software architect before being bitten by the BI bug. His current focus is on ETL and data integration, data quality and MDM, SSAS, SharePoint, and Big Data.
Chris regularly speaks at SQL Saturdays, Code Camps, and other community events. He has authored multiple whitepapers and books and served as technical editor for others.