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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="2014-05-20T18:00:00" datetime="2014-05-20T18:00:00">Tuesday, May 20, 2014 from 6</time>–<time class="dtend dt-end" title="2014-05-20T20:00:00" datetime="2014-05-20T20:00:00">8pm</time></div> <div class="location vcard p-location h-card"> <a class="url" href='http://calagator.org/venues/202393816'><span class='fn org p-name'>Nike World Headquarters - Nolan Ryan</span></a> <div class="adr p-adr h-adr"> <div class="street-address p-street-address">1 Bowerman Dr</div> <span class="locality p-locality">Beaverton</span> , <span class="region p-region">OR</span> <span class="postal-code p-postal-code">97005</span> <div class="country-name p-country-name">US</div> (<a href='https://maps.google.com/maps?q=1%20Bowerman%20Dr,%20Beaverton%20OR%2097005%20US'>map</a>) </div> </div> <div class="description p-description"> <h3>Applied Recommender Systems</h3> <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 focus on an actual Recommender System application and will focus on:</p> <p>Recommender Systems Overview - a quick recap of my January talk on <a href="http://www.slideshare.net/rpbrehm/recommendersystempresentationpjug01212014-32136430">Intro to Recommenders</a>.</p> <ul> <li>Apache Mahout – A production-grade Machine Learning system. One of Mahout's strong use cases is building recommenders.</li> <li><p>Hadoop - Map/Reduce and other tools such as Hive</p></li> <li><p>Spring XD - A Spring.io project to simplify the development of big data applications.</p></li> </ul> <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 Go To Market 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 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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Sunday, May 4, 2014 at 2:38pm.

Portland Java User Group (PJUG)

Tuesday, May 20, 2014 from 6–8pm

Nike World Headquarters - Nolan Ryan

1 Bowerman Dr

Beaverton, OR 97005, US (map)

Doors will be open at 5:30pm for those that may arrive a bit early.

The room is "Air Huarach" in Nolan Ryan building in Nike Campus. The building does not have an address of its own so the participants will have to come to One Bowerman Drive, Beaverton OR and get Directions from Nike Security from there on. I have attached a campus map for reference.

In the lobby of Nolan Ryan building there will be I or somebody else from Nike helping to let people in the building and direct them to the conference room.

Website

http://pjug.org

Description

Applied 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 focus on an actual Recommender System application and will focus on:

Recommender Systems Overview - a quick recap of my January talk on Intro to Recommenders.

Apache Mahout – A production-grade Machine Learning system. One of Mahout's strong use cases is building recommenders.
Hadoop - Map/Reduce and other tools such as Hive
Spring XD - A Spring.io project to simplify the development of big data applications.

Speaker

Bob Brehm is a Java software developer in the Portland area. Most recently he has been contracting with Nike on their Go To Market 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 sports.