SUT-ML.github.io/Psets.html at main · SUT-ML/SUT-ML.github.io · GitHub

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<title>ML: Psets
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      <div class="menu-item"><a href="index.html" class="current">Home</a></div>
      <div class="menu-item"><a href="contact.html">Contact</a></div>
      <div class="menu-item"><a href="CrsStf.html">Course Staff</a></div>

      <div class="menu-category">Course materials and Psets</div>
      <div class="menu-item"><a href="LNs.html">Lecture notes</a></div>
      <div class="menu-item"><a href="Slides.html">Slides</a></div>
      <div class="menu-item"><a href="Psets.html">Problem Sets</a></div>

  <div class="menu-category">Supplementary material</div>
  <div class="menu-item"><a href="https://people.eecs.berkeley.edu/~jrs/189/" target="_blank">CS 189/289A - UC Berkeley</a></div>
  <div class="menu-item"><a href="https://work.caltech.edu/telecourse" target="_blank">Learning from data - Caltech</a></div>
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  <h1>Machine learning theory: Problem Sets
  </h1>
  <div id="subtitle">Sharif university of technology - Mathematics and Computer science department<br />
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  <table class="imgtable"><tr><td>
  <img src="Resources/drawing_book.png" alt="Drawing of books" width="100px" />&nbsp;</td>
  <td align="left"><p>The Total Score for Psets, comprising both theoretical and practical components, is 6 out of 22.
  </p>
  </td></tr></table>


<h2>Spring 2024
</h2>
<ul>
  <li><a href="https://github.com/SUT-ML/Course-material/blob/main/Problem%20sets/%D8%AA%D9%85%D8%B1%DB%8C%D9%86%20%D8%A7%D9%88%D9%84.pdf">Problem Set 1</a></li>
  <li><a href="https://github.com/SUT-ML/Course-material/blob/main/Problem%20sets/%D8%AA%D9%85%D8%B1%DB%8C%D9%86%20%D8%AF%D9%88%D9%85.pdf">Problem Set 2</a></li>
  <li><a href="https://github.com/SUT-ML/Course-material/tree/main/Problem%20sets/%D8%AA%D9%85%D8%B1%DB%8C%D9%86%20%D8%B3%D9%88%D9%85">Problem Set 3</a></li>
  <li><a href="https://github.com/SUT-ML/Course-material/tree/main/Problem%20sets/%D8%AA%D9%85%D8%B1%DB%8C%D9%86%20%DA%86%D9%87%D8%A7%D8%B1%D9%85">Problem Set 4</a></li>
  <li><a href="https://github.com/SUT-ML/Course-material/tree/main/Problem%20sets/%D8%AA%D9%85%D8%B1%DB%8C%D9%86%20%D9%BE%D9%86%D8%AC%D9%85">Problem Set 5</a></li>
  <li><p>Will be uploaded</p></li>
</ul>

<h2>Guidelines for Psets
</h2>
<ul>
<li><p>
  The exercises (both practical and theoretical components) will be delivered via the Quera website. As paper delivery is not feasible, students must prepare a clear image of the theoretical exercise part and upload it to the site.
</p>
</li>
<li><p> If the exercises are sent to the email address of the assistants, please note that no marks will be awarded.
</p>
</li>
<li><p>For practical exercises, utilize only the Python language.
</p>
</li>
<li><p>
  For your well-being, we have considered a 10-day delay allowance for each student due to varying time constraints throughout the semester. This implies that within the semester, you may submit exercises up to 10 days late without grade deduction. It's important to note that for exercises comprising both practical and theoretical components, delays for each part are calculated independently. For instance, if the first exercise consists of practical and theoretical segments and both are submitted one day late, two days will be deducted from your allowance.
</p></li>
<li><p>The upload box on Quora will stay open for each exercise until four days after the deadline for both the theoretical and practical sections. It will not be possible to submit the exercise after this time, regardless of whether you have permission to delay or not.</p></li>

</ul>


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