cube.html

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layout: page
title: The Cube
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<section class="main-container text">
    <div class="main">
        <table class="table">
            <h3>Supervised Learning</h3>
            <br>
            <tr>
              <td class="col-xs-2"></td>
              <th scope="col" class="col-xs-5">Discrete</th>
              <th scope="col" class="col-xs-5">Continuous</th>
            </tr>
            <tr>
              <th scope="row">Probabilistic</th>
              <td>
                <ul>
                  <li><a href="{{ site.baseurl }}/recap5" target="_blank">Lecture 5 - Probabilistic Classification</a></li>
                </ul>
              </td>
              <td>
                <ul>
                  <li><a href="{{ site.baseurl }}/recap3" target="_blank">Lecture 3 - Probabilistic Regression</a></li>
                </ul>
              </td>
            </tr>
            <tr>
              <th scope="row">Nonprobabilistic</th>
              <td>
                <ul>
                  <li><a href="{{ site.baseurl }}/recap1" target="_blank">Lecture 1 - KNN Classification</a></li>
                  <li><a href="{{ site.baseurl }}/recap4" target="_blank">Lecture 4 - Linear Classification</a></li>
                  <li><a href="{{ site.baseurl }}/recap8" target="_blank">Lecture 8 - Neural Networks 1</a></li>
                  <li><a href="{{ site.baseurl }}/recap9" target="_blank">Lecture 9 - Neural Networks 2</a></li>
                  <li><a href="{{ site.baseurl }}/recap10" target="_blank">Lecture 10 - Support Vector Machines 1</li>
                  <li><a href="{{ site.baseurl }}/recap11" target="_blank">Lecture 11 - Support Vector Machines 2</li>
                </ul>
              </td>
              <td>
                <ul>
                  <li><a href="{{ site.baseurl }}/recap1" target="_blank">Lecture 1 - KNN and Kernel Regression</a></li>
                  <li><a href="{{ site.baseurl }}/recap2" target="_blank">Lecture 2 - Linear Regression</a></li>
                  <li><a href="{{ site.baseurl }}/recap8" target="_blank">Lecture 8 - Neural Networks 1</a></li>
                  <li><a href="{{ site.baseurl }}/recap9" target="_blank">Lecture 9 - Neural Networks 2</a></li>
                </ul>
              </td>
            </tr>
        </table>
        <table class="table">
            <h3>Unsupervised Learning</h3>
            <br>
            <tr>
              <td class="col-xs-2"></td>
              <th scope="col" class="col-xs-5">Discrete</th>
              <th scope="col" class="col-xs-5">Continuous</th>
            </tr>
            <tr>
              <th scope="row">Probabilistic</th>
              <td>
                <ul>
                  <li><a href="{{ site.baseurl }}/recap14" target="_blank">Lecture 14 - Mixture Models</a></li>
                </ul>
              </td>
              <td>
                <ul>
                  <li><a href="{{ site.baseurl }}/recap16" target="_blank">Lecture 16 - Topic Models</a></li>
                </ul>
              </td>
            </tr>
            <tr>
              <th scope="row">Nonprobabilistic</th>
              <td>
                <ul>
                  <li><a href="{{ site.baseurl }}/recap13" target="_blank">Lecture 13 - HAC and K-Means</a></li>
                </ul>
              </td>
              <td>
                <ul>
                  <li><a href="{{ site.baseurl }}/recap15" target="_blank">Lecture 15 - Principal Component Analysis</a></li>
                </ul>
              </td>
            </tr>
        </table>
    </div>
</section>