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<!DOCTYPE html>
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<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1">
<title>HSL course material</title>

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<h1 class="title">
AI project
</h1>
<h1>
Course material
</h1>
<ul>

<li><a href="https://kenn7.github.io/AIproject/project/">Artificial Intelligence Project</a></li>

</ul>




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124 changes: 124 additions & 0 deletions AIproject/project/index.html
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<!DOCTYPE html>
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<meta charset="utf-8">
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<h1 class="title">
Artificial Intelligence Project
</h1>
<div class="sub_grid">
<div><button id="print_button" class="no-print button_effect">🖨️(as pdf)</button></div>
<div>v1.0.0</div>
<div class="subtitle">2023-09-15</div>
<div id="all_sol_but_div"></div>
</div>

<h1 id="introduction">Introduction</h1>
<img src="/AIproject/ios_fa.png" alt="Smart image galery" width=30% />
<img src="/AIproject/lightr.png" alt="Smart image galery" width=66% />
<p>Screenshots from <a href="https://support.apple.com/fr-fr/guide/iphone/iph9c7ee918c/ios">iOS Photo app</a> and <a href="https://helpx.adobe.com/lightroom-classic/help/face-recognition.html">Adobe Lightroom</a></p>
<h2 id="smart-image-gallery">Smart image gallery</h2>
<p>We want to create a smart image gallery. Your image galery should have the
following features: Automatic detection of persons and possibly animals.
Identifying a person and being capable of detecting all occurrences of a
specific person accross images, being able to filter by person.</p>
<p>This project is multidisciplinary, you will leverage your knowledge of machine
learning, learn new techniques, and also use your knowledge of programming,
web development, and ergonomics.</p>
<h2 id="features">Features</h2>
<ul>
<li>A web app that allows users to upload and process image files.</li>
<li>The app processes the images and detects humans.</li>
<li>The app detects animals in images.</li>
<li>The app clusters and identifies humans and animals </li>
<li>There is the possibility of tagging or adding custom labels to images for better organization.</li>
<li>It is possible to filter images by humans in them.</li>
<li>It is possible to filter images by types of animals in them.</li>
</ul>
<h2 id="tools">Tools</h2>
<p>You can use any tools you want, both for the web and for the machine learning
parts.
You can use any programming language, any existing dataset you can find online,
any pre-trained machine learning model (do not forget to cite your sources).</p>
<p>One component of the project should include a machine learning model that you have trained.</p>
<p>The report should contain the full technical explanation of the different
machine learning techniques that you will use. It should follow this structure:
Introduction, Materials and methods, Results, Discussion.</p>
<h1 id="evaluation">Evaluation</h1>
<h2 id="grading">Grading</h2>
<p>The project should be done in groups of 2 or 3 students.
The report, presentation, and sources should be uploaded to claco.</p>
<p>The evaluation is separated into 3 parts: </p>
<ul>
<li>how well your app works, its performance on some unseen examples, the machine
learning techniques, including report (50%),</li>
<li>the ergonomics, functionalities and overall look &amp; feel (25%),</li>
<li>the presentation and questions (25%).</li>
</ul>
<h2 id="presentation">Presentation</h2>
<p>As a <strong>group</strong>, you prepare a 15-minute presentation to be presented on December
20.
For the presentation: present your solution, justify your choices, present your results, and make a
demonstration of your app (with possible limitations?).</p>
<p>The presentation will be followed by 15 minutes of questions.</p>



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<p class="footnote">Found an error? Let us know:
<a href="https://github.com/kenn7/kenn7.github.io/">
https://github.com/kenn7/kenn7.github.io/
</a>
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<!DOCTYPE html>
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<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1">
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<h1 class="title">
Algorithms, coding problems.
</h1>
<div class="sub_grid">
<div><button id="print_button" class="no-print button_effect">🖨️(as pdf)</button></div>
<div>v1.0.1</div>
<div class="subtitle">2023-09-15</div>
<div id="all_sol_but_div"></div>
</div>

<h1 id="coding-problem-assignement">Coding problem assignement</h1>
<h2 id="introduction">Introduction</h2>
<p>You should solve some problems from <a href="https://adventofcode.com/">Advent Of Code</a>
2023 edition (starting december 1).
Advent Of Code is an advent calendar for coding exercises, each day of december,
a new problem is unlocked and available for solving. Each problem has 2 levels,
in order to get a double <em>gold</em> star, you need to solve both levels of the problem.</p>
<p>In groups of $n$ student(s) you should get at least $\left\lceil 7 \cdot \log_2 (n+1) \right\rceil$ double gold stars
(with $ 0 &lt; n \leq 3$).</p>
<p>Those exercises account for 30% of your final grade.</p>
<h2 id="submission">Submission</h2>
<p>Please provide a screenshot of your Advent Of Code dashboard showing your user
at the top right (example below for 2020), that shows at least $\left\lceil 7 \cdot \log_2 (n+1) \right\rceil$ double gold stars.</p>
<p>You will upload all your code and your screenshot as an archive on claco.</p>
<img src="/algo/aoc.png" alt="AOC screenshot" width=100% />



</div>
<div class="footer">

<hr>
<p class="footnote">Found an error? Let us know:
<a href="https://github.com/kenn7/kenn7.github.io/">
https://github.com/kenn7/kenn7.github.io/
</a>
</p>


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<!DOCTYPE html>
<html lang="en">

<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1">
<title>HSL course material</title>

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<h1 class="title">
Algorithms and optimization
</h1>
<h1>
Course material
</h1>
<ul>

<li><a href="https://kenn7.github.io/algo/session1/">Algorithms, Session 1, Complexity and divide and conquer</a></li>

<li><a href="https://kenn7.github.io/algo/session2/">Algorithms, Session 2, Data Structures</a></li>

<li><a href="https://kenn7.github.io/algo/session3/">Algorithms, Session 3, Hash Tables</a></li>

<li><a href="https://kenn7.github.io/algo/session4/">Algorithms, Session 4, Recursion, Search</a></li>

<li><a href="https://kenn7.github.io/algo/session5/">Algorithms, Session 5, Dijkstra and A*</a></li>

<li><a href="https://kenn7.github.io/algo/session6/">Algorithms, Session 6, Dynamic Programming</a></li>

<li><a href="https://kenn7.github.io/algo/coding-problems/">Algorithms, coding problems.</a></li>

</ul>

<h1 id="course-slides">Course slides</h1>
<ul>
<li><a href="https://kenn7.github.io/courses/algo/cours1">Course 1, Complexity and divide and conquer</a></li>
<li><a href="https://kenn7.github.io/courses/algo/cours2">Course 2, Data Structures</a></li>
<li><a href="https://kenn7.github.io/courses/algo/cours3">Course 3, Hash Tables</a></li>
<li><a href="https://kenn7.github.io/courses/algo/cours4">Course 4, Search, Optimization</a></li>
<li><a href="https://kenn7.github.io/courses/algo/cours5">Course 5, Recursion and Dynamic Programming</a></li>
</ul>



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