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  <div class="vevent h-event"> <h1 class="summary p-name">OSCON Talk: Analyzing Data with Python with Sarah Guido</h1> <div class='date'><time class="dtstart dt-start" title="2014-07-23T18:30:00" datetime="2014-07-23T18:30:00">Wednesday, July 23, 2014 from 6:30</time>–<time class="dtend dt-end" title="2014-07-23T20:00:00" datetime="2014-07-23T20:00:00">8pm</time></div> <div class="location vcard p-location h-card"> <a class="url" href='http://calagator.org/venues/202394323'><span class='fn org p-name'>Little Bird Technologies</span></a> <div class="adr p-adr h-adr"> <div class="street-address p-street-address">506 SW 6th, Suite 200</div> <span class="locality p-locality">Portland</span> , <span class="region p-region">Oregon</span> <span class="postal-code p-postal-code">97205</span> <div class="country-name p-country-name">US</div> (<a href='https://maps.google.com/maps?q=506%20SW%206th,%20Suite%20200,%20Portland%20Oregon%2097205%20US'>map</a>) </div> </div> <div class="description p-description"> <p>Python is quickly becoming the go-to language for data analysis. There are so many tools out there that it can be overwhelming for those that are new to analyzing data in Python. In this presentation, I’ll discuss several of the best tools for working with data, how to structure a data analysis workflow, and which tools are appropriate for handling different kinds of data. You’ll leave with a good understanding of different data analysis techniques in Python and some ideas to try on your own.</p> <p>I’ll show you examples of each of the following:</p> <ul> <li>Data preprocessing</li> <li>Using Scikit-learn for machine learning</li> <li>Using the Natural Language Toolkit for natural language processing <em>Running MapReduce jobs with MRjob </em>Visualizing our results with matplotlib</li> </ul> </div> <h3>Links</h3> <ul> <li><a class="url u-url" href="http://www.meetup.com/Portland-Data-Science-Group/events/194584542/">Website</a></li> </ul> </div>