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NMEP Fall 2024

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!

Schedule

<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 0</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 (<a href="https://docs.google.com/presentation/d/1IaGEpob6Qa-fMGCZFIUshslQtlx97rVo3ZvB59ddKO8/edit?usp=drive_link">slides</a>)</td>
        <td><span class="label label-yellow"><strong>Homework 1</strong></span>
        <a href="/fa24-nmep/assets/hw1/hw1-review-worksheet.pdf">Neural Networks Review</a>
        <a href="https://drive.google.com/file/d/1Up6oxVNy7W_htigekfo2uYSslChIcEof/view?usp=drive_link">Intro to Pytorch</a>
        <a href="https://drive.google.com/drive/folders/1KQLOSiGAPHW-6ORCwtECIkyfUqdNklSu?usp=drive_link">Word Embeddings</a>
        </td>
        <td>Tim</td>
    </tr>
    <tr>
        <td style="max-width: 30px;">4</td>
        <td>Oct 14</td>
        <td>CNNs <s>& Object Detection</s> (<a href="https://docs.google.com/presentation/d/1FQ-RNjrANvdVjQIY4LFaHAlm9-hNVxRftKNYj56n2K4/edit?usp=sharing">slides</a>)</td>
        <td><span class="label label-yellow"><strong>Homework 2</strong></span>
        <a href="https://github.com/mlberkeley/fa24-nmep-hw2/">Model Zhu</a>
        </td>
        <td>Tejas</td>
    </tr>
    <tr>
        <td style="max-width: 30px;">5</td>
        <td>Oct 21</td>
        <td>No Lecture (social!!)</td>
        <td></td>
        <td></td>
    </tr>
    <tr>
        <td style="max-width: 30px;">6</td>
        <td>Oct 28</td>
        <td>NLP & Transformers 1 (<a href="https://docs.google.com/presentation/d/1fTUTXPFuVr-kULgG36PDJVrSdbRMfSLf_tQGnCGAXUY/edit#slide=id.g2fa7bb19c0a_0_0">slides</a>)</td>
        <td><span class="label label-yellow"><strong>Homework 3</strong></span>
        <a href="https://github.com/tejasprabhune/hw3-transformers">Transformers</a>
        <a href="/fa24-nmep/assets/hw3/hw3-worksheet.pdf">Worksheet</a>
        </td>
        <td>Sara</td>
    </tr>
    <tr>
        <td style="max-width: 30px;">7</td>
        <td>Nov 4</td>
        <td>Transformers 2 (<a href="https://docs.google.com/presentation/d/1-qNWqIUD-ld3ijqEhUexp6Usg_ze39hQXXrmdwLc-nI/edit#slide=id.g2fa7bb19c0a_0_0">slides</a>)</td>
        <td></td>
        <td>Derek</td>
    </tr>
    <tr>
        <td style="max-width: 30px;">8</td>
        <td>Nov 11</td>
        <td>Self-supervised Learning (<a href="https://docs.google.com/presentation/d/1sOigbq6bcI3TIiQD3necn3LrmqJKEJOIoDJnxSN7sfE/edit?usp=drive_link">slides</a>)</td>
        <td><span class="label label-green"><strong>Final Project Proposal</strong></span></td>
        <td>Tejas</td>
    </tr>
    <tr>
        <td style="max-width: 30px;">9</td>
        <td>Nov 18</td>
        <td>RL (<a href="https://docs.google.com/presentation/d/1ewH5WvMKY0v0n8izLtlwmAskf5zdIcOftNFbO6uP474/edit?usp=sharing">slides</a>)</td>
        <td></td>
        <td>Saathvik</td>
    </tr>
    <tr>
        <td style="max-width: 30px;">10</td>
        <td>Nov 25</td>
        <td>Ethics, Object Detection (<a href="https://docs.google.com/presentation/d/1FQ-RNjrANvdVjQIY4LFaHAlm9-hNVxRftKNYj56n2K4/edit?usp=sharing">slides</a>)</td>
        <td><span class="label label-green"><strong>Final Project Checkpoint</strong></span><br><span class="label"><strong>Extra Exercise</strong></span> <a href="https://colab.research.google.com/drive/1nDIw-Kj3_6bvhXpBW_W_jMuoNvJeBVo9?usp=drive_link">YOLO</a></td>
        <td>Tim</td>
    </tr>
    <tr>
        <td style="max-width: 30px;">11</td>
        <td>Dec 2</td>
        <td>GANs (<a href="https://docs.google.com/presentation/d/17QeISP3fi5MZN-n9_-8PKVMe9Q-qrmlwkCOUAXv2LZw/edit?usp=drive_link">slides</a>), Diffusion (<a href="https://docs.google.com/presentation/d/1Dy9_zs4MrgM7w4IY8lrikp_orFUGNYgnwNuhnsGF61o/edit?usp=drive_link">slides</a>)</td>
        <td><span class="label label-red"><strong>NMEP Final</strong></span>
            <a href="https://calendar.google.com/calendar/u/0/appointments/schedules/AcZssZ2OIBta2aWKLomTShrIrXbohnK0j6ERU7zkiJmBsAQrUkBFn2t7we6KJzza3gPvFbhLFP-s44ry">Signups 1</a>
            <a href="https://calendar.google.com/calendar/u/0/appointments/schedules/AcZssZ2Z09UrGFK02sdKhja3VvnVJCc5hSF_9URqSvP038A9YXuKCpjWyzRioGCd683x6U4bngWZARtS">Signups 2</a> (if the other one is full)
            <br><span class="label"><strong>Lecture Exercise</strong></span> <a href="https://github.com/tejasprabhune/lec10-diffusion">Diffusion</a></td>
        <td>Tejas, Nemer</td>
    </tr>
    <tr>
        <td style="max-width: 30px;">12</td>
        <td>Dec 9</td>
        <td>No Lecture (final presentations)</td>
        <td><span class="label label-green"><strong>Final Project Due</strong></span></td>
        <td></td>
    </tr>
</tbody>