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<div class="vevent h-event"> <h1 class="summary p-name">Portland Java User Group (PJUG)</h1> <div class='date'><time class="dtstart dt-start" title="2014-01-21T18:00:00" datetime="2014-01-21T18:00:00">Tuesday, January 21, 2014 from 6</time>–<time class="dtend dt-end" title="2014-01-21T21:00:00" datetime="2014-01-21T21:00:00">9pm</time></div> <div class="location vcard p-location h-card"> <a class="url" href='http://calagator.org/venues/202390558'><span class='fn org p-name'>Oracle (Downtown Campus)</span></a> <div class="adr p-adr h-adr"> <div class="street-address p-street-address">1211 SW 5th Avenue, Suite 800, Room 8005</div> <span class="locality p-locality">Portland</span> , <span class="region p-region">Oregon</span> <span class="postal-code p-postal-code">97204</span> <div class="country-name p-country-name">US</div> (<a href='https://maps.google.com/maps?q=1211%20SW%205th%20Avenue,%20Suite%20800,%20Room%208005,%20Portland%20Oregon%2097204%20US'>map</a>) </div> </div> <div class="description p-description"> <h2>Introduction to Recommender Systems</h2> <p>Ever wonder how Amazon and Netflix seem to have an uncanny ability to anticipate what products you might be interested in based on your past selections? This presentation will delve into how this accomplished thought the use use of filters - both collaborative and content-based - and also hybrid techniques.</p> <p>Two practical open source recommender systems will also be presented:</p> <p>Lenskit framework - An open-source toolkit used primarily for researching and building recommender prototypes.</p> <p>Apache Mahout - A production-grade Machine Learning system. One of Mahout's strong use cases is in building recommenders.</p> <h3>Speaker</h3> <p>Bob Brehm is a Java software developer in the Portland area. Most recently he has been contracting with Nike on their Digital Search team. Bob had dabbled with Java since the early days and got serious about it in 2002. Bob is keenly interested in and has decided to specialize in Enterprise Search, Recommenders and Big Data. Bob is married and has lived in the Portland area since 2001 when he relocated from Rochester, NY. He believes strongly that rain is better than shoveling snow any day! In his spare time Bob enjoys a diverse number of hobbies including electronics, open-source projects, reading, exploring Portland, and running/sports.</p> </div> <h3>Links</h3> <ul> <li><a class="url u-url" href="http://pjug.org">Website</a></li> </ul> </div>

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Wednesday, January 15, 2014 at 12:56am.

Portland Java User Group (PJUG)

Tuesday, January 21, 2014 from 6–9pm

Oracle (Downtown Campus)

1211 SW 5th Avenue, Suite 800, Room 8005

Portland, Oregon 97204, US (map)

Website

http://pjug.org

Description

Introduction to Recommender Systems

Ever wonder how Amazon and Netflix seem to have an uncanny ability to anticipate what products you might be interested in based on your past selections? This presentation will delve into how this accomplished thought the use use of filters - both collaborative and content-based - and also hybrid techniques.

Two practical open source recommender systems will also be presented:

Lenskit framework - An open-source toolkit used primarily for researching and building recommender prototypes.

Apache Mahout - A production-grade Machine Learning system. One of Mahout's strong use cases is in building recommenders.

Speaker

Bob Brehm is a Java software developer in the Portland area. Most recently he has been contracting with Nike on their Digital Search team. Bob had dabbled with Java since the early days and got serious about it in 2002. Bob is keenly interested in and has decided to specialize in Enterprise Search, Recommenders and Big Data. Bob is married and has lived in the Portland area since 2001 when he relocated from Rochester, NY. He believes strongly that rain is better than shoveling snow any day! In his spare time Bob enjoys a diverse number of hobbies including electronics, open-source projects, reading, exploring Portland, and running/sports.