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pdtxie committed Oct 1, 2024
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Welcome everyone!
In the New Member Education Program (NMEP), we'll be paving a sturdy ML foundation for you—from classical ML to diffusion models. Come hungry to learn and get to know the rest of your class!

Your instructors this semester are Tejas Prabhune and [Tim Xie](https://tim-xie.com)!


### Schedule
Expand All @@ -22,95 +23,97 @@ In the New Member Education Program (NMEP), we'll be paving a sturdy ML foundati
<col span="1" style="width: 150px;">
</colgroup>

<tr> <th style="max-width: 30px;">Week</th> <th>Date</th> <th>Lecture</th> <th>Assignments</th> <th>Lecturer(s)</th> </tr>
<tr>
<td style="max-width: 30px;">1</td>
<td>Sep 23</td>
<td>Intro + Background Review (<a href="https://docs.google.com/presentation/d/16QicPaSS0YFcJvTFSn1yea5n_ORVMcbxCHjeDyoQSKg/edit?usp=drive_link">slides</a>)</td>
<td><span class="label"><strong>Lecture Exercise</strong></span> <a href="https://drive.google.com/file/d/1UM2w5BrJrEcI69_eqhIn-t1yrdC7XzY9/view?usp=drive_link">Rockfall</a><br>
<span class="label label-yellow"><strong>Homework 1</strong></span>
<a href="/fa24-nmep/assets/hw0/hw0-math.pdf">Math Review</a>
<a href="/fa24-nmep/assets/hw0/hw0-pandas.ipynb">Pandas</a>
<a href="/fa24-nmep/assets/hw0/hw0-numpy.ipynb">Numpy</a></td>
<td>Tim, Tejas</td>
</tr>
<tr>
<td style="max-width: 30px;">2</td>
<td>Sep 30</td>
<td>Classical ML (<a href="https://docs.google.com/presentation/d/13NwgyAVt6c79NgEvChtRHKd2ntMheDY2qmMQlMmAAS4/edit?usp=drive_link">slides</u>)</td>
<td></td>
<td>Tejas</td>
</tr>
<tr>
<td style="max-width: 30px;">3</td>
<td>Oct 7</td>
<td>Deep Learning, Embeddings</td>
<td></td>
<td>Tim</td>
</tr>
<tr>
<td style="max-width: 30px;">4</td>
<td>Oct 14</td>
<td>CNNs & Object Detection</td>
<td></td>
<td>Saathvik</td>
</tr>
<tr>
<td style="max-width: 30px;">5</td>
<td>Oct 21</td>
<td>NLP & Transformers 1</td>
<td></td>
<td>Chuyi, Sara</td>
</tr>
<tr>
<td style="max-width: 30px;">6</td>
<td>Oct 28</td>
<td>Transformers 2</td>
<td></td>
<td></td>
</tr>
<tr>
<td style="max-width: 30px;">7</td>
<td>Nov 4</td>
<td>Self-supervised Learning</td>
<td></td>
<td>Tejas</td>
</tr>
<tr>
<td style="max-width: 30px;">8</td>
<td>Nov 11</td>
<td>RL</td>
<td></td>
<td>Luca</td>
</tr>
<tr>
<td style="max-width: 30px;">9</td>
<td>Nov 18</td>
<td>GANs, Diffusion</td>
<td></td>
<td>Mehdi, Nemer</td>
</tr>
<tr>
<td style="max-width: 30px;">10</td>
<td>Nov 25</td>
<td>Ethics</td>
<td></td>
<td></td>
</tr>
<tr>
<td style="max-width: 30px;">11</td>
<td>Dec 2</td>
<td>Special Topics</td>
<td></td>
<td></td>
</tr>
<tr>
<td style="max-width: 30px;">12</td>
<td>Dec 9</td>
<td>(No Lecture) Final Presentations</td>
<td></td>
<td></td>
</tr>
<tbody>
<tr> <th style="max-width: 30px;">Week</th> <th>Date</th> <th>Lecture</th> <th>Assignments</th> <th>Lecturer(s)</th> </tr>
<tr>
<td style="max-width: 30px;">1</td>
<td>Sep 23</td>
<td>Intro + Background Review (<a href="https://docs.google.com/presentation/d/16QicPaSS0YFcJvTFSn1yea5n_ORVMcbxCHjeDyoQSKg/edit?usp=drive_link">slides</a>)</td>
<td><span class="label"><strong>Lecture Exercise</strong></span> <a href="https://drive.google.com/file/d/1UM2w5BrJrEcI69_eqhIn-t1yrdC7XzY9/view?usp=drive_link">Rockfall</a><br>
<span class="label label-yellow"><strong>Homework 1</strong></span>
<a href="/fa24-nmep/assets/hw0/hw0-math.pdf">Math Review</a>
<a href="/fa24-nmep/assets/hw0/hw0-pandas.ipynb">Pandas</a>
<a href="/fa24-nmep/assets/hw0/hw0-numpy.ipynb">Numpy</a></td>
<td>Tim, Tejas</td>
</tr>
<tr>
<td style="max-width: 30px;">2</td>
<td>Sep 30</td>
<td>Classical ML (<a href="https://docs.google.com/presentation/d/13NwgyAVt6c79NgEvChtRHKd2ntMheDY2qmMQlMmAAS4/edit?usp=drive_link">slides</a>)</td>
<td></td>
<td>Tejas</td>
</tr>
<tr>
<td style="max-width: 30px;">3</td>
<td>Oct 7</td>
<td>Deep Learning, Embeddings</td>
<td></td>
<td>Tim</td>
</tr>
<tr>
<td style="max-width: 30px;">4</td>
<td>Oct 14</td>
<td>CNNs & Object Detection</td>
<td></td>
<td>Saathvik</td>
</tr>
<tr>
<td style="max-width: 30px;">5</td>
<td>Oct 21</td>
<td>NLP & Transformers 1</td>
<td></td>
<td>Chuyi, Sara</td>
</tr>
<tr>
<td style="max-width: 30px;">6</td>
<td>Oct 28</td>
<td>Transformers 2</td>
<td></td>
<td></td>
</tr>
<tr>
<td style="max-width: 30px;">7</td>
<td>Nov 4</td>
<td>Self-supervised Learning</td>
<td></td>
<td>Tejas</td>
</tr>
<tr>
<td style="max-width: 30px;">8</td>
<td>Nov 11</td>
<td>RL</td>
<td></td>
<td>Luca</td>
</tr>
<tr>
<td style="max-width: 30px;">9</td>
<td>Nov 18</td>
<td>GANs, Diffusion</td>
<td></td>
<td>Mehdi, Nemer</td>
</tr>
<tr>
<td style="max-width: 30px;">10</td>
<td>Nov 25</td>
<td>Ethics</td>
<td></td>
<td></td>
</tr>
<tr>
<td style="max-width: 30px;">11</td>
<td>Dec 2</td>
<td>Special Topics</td>
<td></td>
<td></td>
</tr>
<tr>
<td style="max-width: 30px;">12</td>
<td>Dec 9</td>
<td>(No Lecture) Final Presentations</td>
<td></td>
<td></td>
</tr>
</tbody>
</table>


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