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  <div class="vevent h-event"> <h1 class="summary p-name">Portland Deep Learning: Peer mentoring discussion + Matt Boyd w/ overview of setting up a project.</h1> <div class='date'><time class="dtstart dt-start" title="2017-12-13T18:00:00" datetime="2017-12-13T18:00:00">Wednesday, December 13, 2017 from 6</time>–<time class="dtend dt-end" title="2017-12-13T20:00:00" datetime="2017-12-13T20:00:00">8pm</time></div> <div class="location vcard p-location h-card"> <a class="url" href='http://calagator.org/venues/202395744'><span class='fn org p-name'>Tura.io</span></a> <div class="adr p-adr h-adr"> <div class="street-address p-street-address">2828 Southwest Corbett Avenue</div> <span class="locality p-locality">Portland</span> , <span class="region p-region">OR</span> <span class="postal-code p-postal-code">97201</span> <div class="country-name p-country-name">US</div> (<a href='https://maps.google.com/maps?q=2828%20Southwest%20Corbett%20Avenue,%20Portland%20OR%2097201%20US'>map</a>) </div> </div> <div class="description p-description"> <p>Lets get together to discuss all aspects of deep learning and any questions you may have on the Fast.AI or Andrew Ng's coursera course.</p> <p>Also our own Matt Boyd will lead a discussion on:</p> <p>"What I've found that works and can still be improved"</p> <p>Matt will do a brief overview of the general approach to setting up a deep learning Kaggle project, touch on 2 or 3 good practices to follow, and throw around some ideas of what to improve.</p> <p>Mat will cover how to index the data and build train/validation sets, finding the right balance of augmentation, and strategies for keeping results for 50+ different models straight.</p> <p>All levels of experience are welcome. We rarely have presentations, though we may someone lead a discussion. Bring your questions, projects and ideas, basic or advanced, and we'll try to help.</p> </div> <h3>Links</h3> <ul> <li><a class="url u-url" href="https://www.meetup.com/Portland-Deep-Learning/events/245109147/">Website</a></li> </ul> </div>