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<h2><a>Metis week 3: Gradient Descent into Hell</a></h2>
<p>"Never Stop Never stopping"</p>
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<time class="published" datetime="2018-07-20">July 20, 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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<i>Weeks 2 & 3 were intense. Model-selection, regression methods, probability theory, and modeling leading to the second project. </i>
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<pbu> Week 2 & 3 </pbu>
<p> In just three weeks….Workflow ready! Fundamentals set! Regression let’s go! </p>
<p>The second week was theory and mechanics: probability theory, hypothesis testing, regression & model evaluation in statsmodels, and scikit-learn. Some guidance towards interactive design and design thinking, which led to my second project focusing on regression, statistics, and probability. For data acquisition, I employed web scraping via BeautifulSoup, & a Selenium bot, storing most of the data in Pythonic flat files. Details will follow in subsequent posts as well as the Financial Singularity discussion. </p>
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<pb> Gradient Descent into Hell </pb>
<p> Let’s talk about week 3….The highlight of the week was cross-validation methodologies for model-selection combined with the “Train- Test-Split” procedure for regression modeling. After a foray with Bayes Theorem we learned regularization regression methods—lasso, ridge, and elastic net. I expected an intimidating tide of mathematics, but its possible to understand it with a little bit of calculus and a spoonful of statistics. This week I wrote more lines of code than ever in my life and I had a lot of fun plotting with matplotlib and seaborn. After several code-dense lectures, we ended the week on a much lighter note with Probability theory…. followed by some Korean BBQ and karaoke with my peers. </p>
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Coming soon: #FinancialSingularity, #RegressionProject
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