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<html>
<head>
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<h3>Home</h3>
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<h3>Resume</h3>
<p>Data Scientist & Investment Professional</p>
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<h3>About Me</h3>
<p> A few more details...</p>
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<p>Prior blog posts</p>
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<h2><a href="/GME_EA.html">GameStop vs. Electronic Arts</a></h2>
<p>Regression Modeling</p>
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<time class="published" datetime="2018-10-12">October 12, 2018</time>
<a href="about.html" class="author"><span class="name">Clarence Stephen</span><img src="images/avatar.jpg" alt="" /></a>
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<a href="/GME_EA.html" class="image featured"><img src="images/GME_EA/samus.png" style ="width:90%; margin-left:5%"alt="" /></a>
<p> Analyzed influence of GameStop's review scores on EA stock performance using a polynomial regression model and
obtained R^2 value of 0.976. (BeautifulSoup, Selenium, StatsModels, Scikit-Learn)</p>
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<time class="published" datetime="2018-09-28">Septemeber 28, 2018</time>
<a href="about.html" class="author"><span class="name">Clarence Stephen</span><img src="images/avatar.jpg" alt="" /></a>
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<a href="/BetterReads.html" class="image featured"><img src="images/betterreads/betterreads.png" style ="width:90%; margin-left:5%" alt="" /></a>
<p> A 4 minute presentation on my book recommendation system, built using data extracted from 26m Amazon book reviews and 6m Goodreads reviews. Used collaborative filtering via implicit ALS algorithm to build ensemble of 5 models on user:user, user:item, and item:item vectors. (AWS, Big Data, MongoDB, PySpark, PyTorch, Spotlight, Implicit, Cython, OpenMP)</p>
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<h2><a href="/MTA.html">MTA Traffic Analysis</a></h2>
<p>Data Wrangling & Visualization</p>
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<time class="published" datetime="2018-08-15">August 15, 2018</time>
<a href="about.html" class="author"><span class="name">Clarence Stephen</span><img src="images/avatar.jpg" alt="" /></a>
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<a href="/MTA.html" class="image featured"><img src="images/DOHS.png" alt="" style ="width:90%; margin-left:5%" /></a>
<p>MTA Traffic Analysis: Data cleaning, exploratory analysis, and visualization of MTA turnstile data to find areas
of heavy traffic in NYC subway stations. (Matplotlib, pandas, seaborn)</p>
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<h2><a href="/2018-07-30_Financial_Singularity.html">Financial Singularity</a></h2>
<p>Machine Learning in Financial Markets</p>
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<time class="published" datetime="2018-07-30">July 30, 2018</time>
<a href="about.html" class="author"><span class="name">Clarence Stephen</span><img src="images/avatar.jpg" alt="" /></a>
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<p>"Not all problems can be solved; just because you’ve assembled examples of inputs X and targets Y doesn’t mean X
contains enough information to predict Y. For instance, if you’re trying to predict the movements of a stock on the
stock market given its recent price history, you’re unlikely to succeed, because price history doesn’t contain much
predictive information."</p>
<p><i> --Francois Chollet, “Deep Learning with Python"</i> </p>
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<h2><a href="/2018-07-27_Facebook.html">Let's talk about Facebook</a></h2>
<p>To buy or not to buy...</p>
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<time class="published" datetime="2018-07-27">July 27, 2018</time>
<a href="about.html" class="author"><span class="name">Clarence Stephen</span><img src="images/avatar.jpg" alt="" /></a>
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<p>Wait-and-see: Facebook is undergoing a significant strategy shift and it may be best to stay on the sidelines for
now</p>
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<h2>Cognosis</h2>
<p>#FactsMatter</p>
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<div class="LI-profile-badge" data-version="v1" data-size="medium" data-locale="en_US" data-type="vertical" data-theme="light" data-vanity="clarencestephen"><a class="LI-simple-link" href='https://www.linkedin.com/in/clarencestephen?trk=profile-badge'>Clarence Stephen</a></div>
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<h2>About</h2>
<p>Data Scientist, Investment Professional, & Bookworm with a passion for quantitatively driven solutions and over a decade of experience in multi-asset trading.</p>
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<h3><a href="GME_EA.html">GameStop vs. Electronic Arts</a></h3>
<time class="published" datetime="2018-10-12">October 12, 2018</time>
</header>
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<h3><a href="BetterReads.html">Better Reads</a></h3>
<time class="published" datetime="2018-09-28">September 28, 2018</time>
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<time class="published" datetime="2018-08-15">August 15, 2018</time>
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<h3><a href="/2018-07-30_Financial_Singularity.html">Financial Singularity</a></h3>
<time class="published" datetime="2018-07-30">July 30, 2018</time>
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<h3><a href="/2018-07-27_Facebook.html">Let's talk about Facebook</a></h3>
<time class="published" datetime="2018-07-27">July 27, 2018</time>
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<h3><a href="/2018-07-20_Metis_through_week_3.html">Metis through week 3</a></h3>
<time class="published" datetime="2018-07-20">July 20, 2018</time>
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<h3><a href="/2018-07-11_Metis_First_Week.html">Metis Week One</a></h3>
<time class="published" datetime="2018-07-20">July 11, 2018</time>
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