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(This article was first published on <strong><a href="http://blog.revolutionanalytics.com/2017/11/recap-earl-boston-2017.html"> Revolutions</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
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<p><em>By Emmanuel Awa, Francesca Lazzeri and Jaya Mathew, data scientists at Microsoft</em></p>
<p>A few of us got to attend <a rel="nofollow" href="https://earlconf.com/boston/" target="_blank">EARL conference</a> in Boston last week which brought together a group of talented users of R from academia and industry. The conference highlighted various Enterprise Applications of R. Despite being a small conference, the quality of the talks were great and showcased various innovative ways in using some of the newer packages available for use in the R language. Some of the attendees were veteran R users while some were new comers to the R language, so there was a mix in the level of proficiency in using the R language.  </p>
<p>R currently has a vibrant community of users and there are over 11,000 open source packages. The conference also encouraged women to join their local chapter for <a rel="nofollow" href="https://rladies.org/" target="_blank">R Ladies</a> with the aim of increasing the participation of women at R conferences and increasing the number of women who contribute <a rel="nofollow" href="https://cran.r-project.org/" target="_blank">R packages</a> to the open source community.</p>
<p>The team from Microsoft got to showcase some of our tools namely the <a rel="nofollow" href="https://docs.microsoft.com/en-us/machine-learning-server/what-is-machine-learning-server" target="_blank">Microsoft ML Server</a> and our commitment to support the open language R. Some of the Microsoft earned sessions were:</p>
<ol>
<li>Deep Learning with R – Francesca Lazzeri</li>
<li>Enriching your Customer profile at Scale using R Server – Jaya Mathew, Emmanuel Awa &amp; Robert Alexander</li>
<li>Developing Deep Learning Applications with CNTK – Ali Zaidi</li>
</ol>
<p>Microsoft was a sponsor at the event and had a booth at the conference where there was a live demo using the Cognitive Services APIs — <a rel="nofollow" href="https://azure.microsoft.com/en-us/services/cognitive-services/face/" target="_blank">namely the Face API</a> — to detect age, gender, facial expression.</p>
<p>In addition, some of the other interesting talks were:</p>
<ol>
<li>When and Why to Use Shiny for Commercial Applications – Tanya Cashorali</li>
<li>HR Analytics: Using Machine Learning to Predict Employee Turnover – Matt Dancho</li>
<li>Using R to Automate the Classification of E-commerce Products – Aidan Boland</li>
<li>Leveraging More Data using Data Fusion in R – Michael Conklin</li>
</ol>
<p>All the slides from the conference will be available at the <a rel="nofollow" href="https://earlconf.com/boston/" target="_blank">conference website</a> shortly. For photos from the conference, visit EARL’s <a rel="nofollow" href="https://twitter.com/earlconf" target="_blank">twitter page</a>.</p>
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