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This presentation provides tools and techniques for doing “data-intensive” science in your own home – much as the gentlemen scientists of the early modern era – using open source software and repurposed commodity hardware. Based on the author’s own experience as a non-specialist practitioner, the presentation gives new data scientists a quick overview of Linux, Hadoop, Mahout, and related software and guidelines for setting up a test and dev environment for tackling meaningful problems in machine learning.
Vin is responsible for enterprise-focused marketing strategy of open source software on Intel architectures. In this role, Vin drives awareness of Intel technologies into the open source ecosystem, and collaborates with OEM and OSV partners to deliver open source solutions to enterprises worldwide. Before Intel, Vin worked at HP for 15 years, most recently as the strategic product planner for open source and Linux on HP ProLiant servers. Vin has an academic background in history of technology and electrical engineering.
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