Morten Hjorth-Jensen
698 lines
35 KiB
HTML
698 lines
35 KiB
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Applied Data Analysis and Machine Learning
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</a>
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</li>
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</ul>
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<p aria-level="2" class="caption" role="heading"><span class="caption-text">About the course</span></p>
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<li class="toctree-l1"><a class="reference internal" href="schedule.html">Teaching schedule with links to material</a></li>
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<li class="toctree-l1"><a class="reference internal" href="textbooks.html">Textbooks</a></li>
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<p aria-level="2" class="caption" role="heading"><span class="caption-text">Review of Statistics with Resampling Techniques and Linear Algebra</span></p>
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<ul class="nav bd-sidenav">
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<li class="toctree-l1"><a class="reference internal" href="statistics.html">1. Elements of Probability Theory and Statistical Data Analysis</a></li>
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<li class="toctree-l1"><a class="reference internal" href="linalg.html">2. Linear Algebra, Handling of Arrays and more Python Features</a></li>
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</ul>
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<p aria-level="2" class="caption" role="heading"><span class="caption-text">From Regression to Support Vector Machines</span></p>
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<ul class="nav bd-sidenav">
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<li class="toctree-l1"><a class="reference internal" href="chapter1.html">3. Linear Regression</a></li>
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<li class="toctree-l1"><a class="reference internal" href="chapter2.html">4. Ridge and Lasso Regression</a></li>
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<li class="toctree-l1"><a class="reference internal" href="chapter3.html">5. Resampling Methods</a></li>
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<li class="toctree-l1"><a class="reference internal" href="chapter4.html">6. Logistic Regression</a></li>
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<li class="toctree-l1"><a class="reference internal" href="chapteroptimization.html">7. Optimization, the central part of any Machine Learning algortithm</a></li>
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<li class="toctree-l1"><a class="reference internal" href="chapter5.html">8. Support Vector Machines, overarching aims</a></li>
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</ul>
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<p aria-level="2" class="caption" role="heading"><span class="caption-text">Decision Trees, Ensemble Methods and Boosting</span></p>
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<ul class="nav bd-sidenav">
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<li class="toctree-l1"><a class="reference internal" href="chapter6.html">9. Decision trees, overarching aims</a></li>
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<li class="toctree-l1"><a class="reference internal" href="chapter7.html">10. Ensemble Methods: From a Single Tree to Many Trees and Extreme Boosting, Meet the Jungle of Methods</a></li>
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</ul>
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<p aria-level="2" class="caption" role="heading"><span class="caption-text">Dimensionality Reduction</span></p>
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<ul class="nav bd-sidenav">
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<li class="toctree-l1"><a class="reference internal" href="chapter8.html">11. Basic ideas of the Principal Component Analysis (PCA)</a></li>
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<li class="toctree-l1"><a class="reference internal" href="clustering.html">12. Clustering and Unsupervised Learning</a></li>
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</ul>
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<p aria-level="2" class="caption" role="heading"><span class="caption-text">Deep Learning Methods</span></p>
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<li class="toctree-l1"><a class="reference internal" href="chapter9.html">13. Neural networks</a></li>
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<li class="toctree-l1"><a class="reference internal" href="chapter10.html">14. Building a Feed Forward Neural Network</a></li>
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<li class="toctree-l1"><a class="reference internal" href="chapter11.html">15. Solving Differential Equations with Deep Learning</a></li>
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<li class="toctree-l1"><a class="reference internal" href="chapter12.html">16. Convolutional Neural Networks</a></li>
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<li class="toctree-l1"><a class="reference internal" href="chapter13.html">17. Recurrent neural networks: Overarching view</a></li>
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</ul>
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<p aria-level="2" class="caption" role="heading"><span class="caption-text">Weekly material, notes and exercises</span></p>
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<ul class="current nav bd-sidenav">
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<li class="toctree-l1"><a class="reference internal" href="exercisesweek34.html">Exercises week 34</a></li>
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<li class="toctree-l1"><a class="reference internal" href="week34.html">Week 34: Introduction to the course, Logistics and Practicalities</a></li>
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<li class="toctree-l1"><a class="reference internal" href="exercisesweek35.html">Exercises week 35</a></li>
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<li class="toctree-l1"><a class="reference internal" href="week35.html">Week 35: From Ordinary Linear Regression to Ridge and Lasso Regression</a></li>
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<li class="toctree-l1"><a class="reference internal" href="exercisesweek36.html">Exercises week 36</a></li>
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<li class="toctree-l1"><a class="reference internal" href="week36.html">Week 36: Linear Regression and Statistical interpretations</a></li>
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<li class="toctree-l1"><a class="reference internal" href="exercisesweek37.html">Exercises week 37</a></li>
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<li class="toctree-l1"><a class="reference internal" href="week37.html">Week 37: Statistical interpretations and Resampling Methods</a></li>
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<li class="toctree-l1"><a class="reference internal" href="exercisesweek38.html">Exercises week 38</a></li>
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<li class="toctree-l1"><a class="reference internal" href="week38.html">Week 38: Logistic Regression and Optimization</a></li>
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<li class="toctree-l1"><a class="reference internal" href="exercisesweek39.html">Exercises week 39</a></li>
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<li class="toctree-l1"><a class="reference internal" href="week39.html">Week 39: Optimization and Gradient Methods</a></li>
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<li class="toctree-l1"><a class="reference internal" href="week40.html">Week 40: Gradient descent methods (continued) and start Neural networks</a></li>
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<li class="toctree-l1"><a class="reference internal" href="exercisesweek41.html">Exercises week 41</a></li>
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<li class="toctree-l1"><a class="reference internal" href="week41.html">Week 41 Neural networks and constructing a neural network code</a></li>
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<li class="toctree-l1"><a class="reference internal" href="exercisesweek42.html">Exercises week 42</a></li>
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<li class="toctree-l1"><a class="reference internal" href="week42.html">Week 42 Constructing a Neural Network code with examples</a></li>
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<li class="toctree-l1"><a class="reference internal" href="additionweek42.html">Exercises Week 42: Logistic Regression and Optimization, reminders from week 38 and week 40</a></li>
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<li class="toctree-l1"><a class="reference internal" href="week43.html">Week 43: Deep Learning: Constructing a Neural Network code and solving differential equations</a></li>
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<li class="toctree-l1"><a class="reference internal" href="exercisesweek43.html">Exercises week 43</a></li>
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<li class="toctree-l1"><a class="reference internal" href="week44.html">Week 44, Convolutional Neural Networks (CNN)</a></li>
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<li class="toctree-l1"><a class="reference internal" href="week45.html">Week 45, Convolutional Neural Networks (CCNs) and Recurrent Neural Networks (RNNs)</a></li>
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<li class="toctree-l1"><a class="reference internal" href="week46.html">Week 46: Decision Trees, Ensemble methods and Random Forests</a></li>
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<li class="toctree-l1"><a class="reference internal" href="week47.html">Week 47: From Decision Trees to Ensemble Methods, Random Forests and Boosting Methods</a></li>
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<li class="toctree-l1"><a class="reference internal" href="exercisesweek47.html">Exercise week 47</a></li>
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<li class="toctree-l1"><a class="reference internal" href="week48.html">Week 48: Gradient boosting and summary of course</a></li>
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<li class="toctree-l1 current active"><a class="current reference internal" href="#">Exercises week 48</a></li>
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</ul>
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<p aria-level="2" class="caption" role="heading"><span class="caption-text">Projects</span></p>
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<li class="toctree-l1"><a class="reference internal" href="project1.html">Project 1 on Machine Learning, deadline October 7 (midnight), 2024</a></li>
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<li class="toctree-l1"><a class="reference internal" href="project2.html">Project 2 on Machine Learning, deadline November 4 (Midnight)</a></li>
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<li class="toctree-l1"><a class="reference internal" href="project3.html">Project 3 on Machine Learning, deadline December 9 (midnight), 2024</a></li>
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<h1>Exercises week 48</h1>
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<h2> Contents </h2>
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<li class="toc-h1 nav-item toc-entry"><a class="reference internal nav-link" href="#">Exercises week 48</a></li>
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<li class="toc-h1 nav-item toc-entry"><a class="reference internal nav-link" href="#overarching-aims-of-the-exercises-this-week">Overarching aims of the exercises this week</a><ul class="visible nav section-nav flex-column">
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#why-did-you-choose-this-course">Why did you choose this course?</a></li>
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#what-was-your-programming-knowledge-before-you-started">What was your programming knowledge before you started?</a></li>
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#how-do-you-judge-your-own-level-of-knowledge-on-machine-learning-before-and-after-this-course">How do you judge your own level of knowledge on machine learning before and after this course?</a></li>
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#did-the-projects-and-the-teaching-material-allow-you-to-deepen-your-insights-about-machine-learning-methods">Did the projects and the teaching material allow you to deepen your insights about Machine Learning methods?</a></li>
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#project-based-teaching-and-active-learning">Project based teaching and active learning</a></li>
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#usefulness-of-the-weekly-exercises">Usefulness of the weekly exercises</a></li>
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#lab-sessions-and-lectures">Lab sessions and lectures</a></li>
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#how-would-you-improve-this-course">How would you improve this course?</a></li>
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#then-some-basic-questions">Then some basic questions</a><ul class="nav section-nav flex-column">
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#which-is-your-preferred-information-chanel-canvas-discord-mail-or-other">Which is your preferred information chanel, Canvas, Discord, mail or other?</a></li>
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#was-the-weekly-update-with-plans-etc-useful">Was the weekly update with plans etc useful?</a></li>
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#was-it-easy-to-access-the-course-material">Was it easy to access the course material?</a></li>
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#which-resources-and-tools-did-you-use-jupyter-notebooks-github-the-various-textbooks-we-have-recommended-etc-etc">Which resources and tools did you use? Jupyter-notebooks, GitHub, the various textbooks we have recommended, etc etc</a></li>
|
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#if-you-did-not-attend-the-lectures-or-the-lab-sessions-which-resources-did-you-use">If you did not attend the lectures or the lab sessions, which resources did you use?</a></li>
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#any-other-topics-impressions-ideas-etc-you-would-like-to-share-with-us">Any other topics, impressions, ideas etc you would like to share with us?</a></li>
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<!-- dom:TITLE: Exercises week 48 --><section class="tex2jax_ignore mathjax_ignore" id="exercises-week-48">
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<h1>Exercises week 48<a class="headerlink" href="#exercises-week-48" title="Link to this heading">#</a></h1>
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<p><strong>November 25-29, 2024</strong></p>
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<p>Date: <strong>Deadline is Friday November 29 at midnight</strong></p>
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</section>
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<section class="tex2jax_ignore mathjax_ignore" id="overarching-aims-of-the-exercises-this-week">
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<h1>Overarching aims of the exercises this week<a class="headerlink" href="#overarching-aims-of-the-exercises-this-week" title="Link to this heading">#</a></h1>
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<p>The exercise this week is a simple course survey and feedback. This
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is important for us in order to improve our teaching material, the
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active learning format and anything else related to a succesful
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mastering of central machine learning methods and their applications.</p>
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<section id="why-did-you-choose-this-course">
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<h2>Why did you choose this course?<a class="headerlink" href="#why-did-you-choose-this-course" title="Link to this heading">#</a></h2>
|
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</section>
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<section id="what-was-your-programming-knowledge-before-you-started">
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<h2>What was your programming knowledge before you started?<a class="headerlink" href="#what-was-your-programming-knowledge-before-you-started" title="Link to this heading">#</a></h2>
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<p>And do you feel this course added to your programming competences and skills?</p>
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</section>
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<section id="how-do-you-judge-your-own-level-of-knowledge-on-machine-learning-before-and-after-this-course">
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<h2>How do you judge your own level of knowledge on machine learning before and after this course?<a class="headerlink" href="#how-do-you-judge-your-own-level-of-knowledge-on-machine-learning-before-and-after-this-course" title="Link to this heading">#</a></h2>
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<p>Here you can discuss your level of skill/knowledge at the start of course
|
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and at the end of the course and how these matched the level of
|
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skill/knowledge needed to complete the projects.</p>
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</section>
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<section id="did-the-projects-and-the-teaching-material-allow-you-to-deepen-your-insights-about-machine-learning-methods">
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<h2>Did the projects and the teaching material allow you to deepen your insights about Machine Learning methods?<a class="headerlink" href="#did-the-projects-and-the-teaching-material-allow-you-to-deepen-your-insights-about-machine-learning-methods" title="Link to this heading">#</a></h2>
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<p>Feel free to comment here.</p>
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</section>
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<section id="project-based-teaching-and-active-learning">
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<h2>Project based teaching and active learning<a class="headerlink" href="#project-based-teaching-and-active-learning" title="Link to this heading">#</a></h2>
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<p>This is a project based course and we as teachers would like to keep
|
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it as it is since we see very clearly that people who attend this
|
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course have a very good learning outcome. Project based courses are
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however demanding (and expensive seen from the university admin) when
|
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it comes to proper feedback and evaluations. Feel free to discuss
|
|
whether you found a project-based useful. Feel also free to comment upon things we can improve upon or
|
|
alternative ways to assess whether the learning outcomes have been
|
|
achieved. Would you for example prefer a standard 4 hours written exam
|
|
be something you would prefer? Or other alternatives to projects? We
|
|
would very much value your thoughts here since projects are an
|
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essential part of this course.</p>
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</section>
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<section id="usefulness-of-the-weekly-exercises">
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<h2>Usefulness of the weekly exercises<a class="headerlink" href="#usefulness-of-the-weekly-exercises" title="Link to this heading">#</a></h2>
|
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<p>Did the weekly exercises help in getting started with the projects?
|
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How relevant where they for solving the projects? Feel free to
|
|
elaborate</p>
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</section>
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<section id="lab-sessions-and-lectures">
|
|
<h2>Lab sessions and lectures<a class="headerlink" href="#lab-sessions-and-lectures" title="Link to this heading">#</a></h2>
|
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<p>Was there a good link between lectures and lab sessions?
|
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Feel
|
|
free to comment.</p>
|
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</section>
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<section id="how-would-you-improve-this-course">
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<h2>How would you improve this course?<a class="headerlink" href="#how-would-you-improve-this-course" title="Link to this heading">#</a></h2>
|
|
<p>Are there topics which are missing, topics which could have been
|
|
omitted and/or discussed in more depth? Feel free to add your comments
|
|
here such as how to improve to teaching material and more.</p>
|
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</section>
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<section id="then-some-basic-questions">
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<h2>Then some basic questions<a class="headerlink" href="#then-some-basic-questions" title="Link to this heading">#</a></h2>
|
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<section id="which-is-your-preferred-information-chanel-canvas-discord-mail-or-other">
|
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<h3>Which is your preferred information chanel, Canvas, Discord, mail or other?<a class="headerlink" href="#which-is-your-preferred-information-chanel-canvas-discord-mail-or-other" title="Link to this heading">#</a></h3>
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</section>
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<section id="was-the-weekly-update-with-plans-etc-useful">
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<h3>Was the weekly update with plans etc useful?<a class="headerlink" href="#was-the-weekly-update-with-plans-etc-useful" title="Link to this heading">#</a></h3>
|
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</section>
|
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<section id="was-it-easy-to-access-the-course-material">
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<h3>Was it easy to access the course material?<a class="headerlink" href="#was-it-easy-to-access-the-course-material" title="Link to this heading">#</a></h3>
|
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</section>
|
|
<section id="which-resources-and-tools-did-you-use-jupyter-notebooks-github-the-various-textbooks-we-have-recommended-etc-etc">
|
|
<h3>Which resources and tools did you use? Jupyter-notebooks, GitHub, the various textbooks we have recommended, etc etc<a class="headerlink" href="#which-resources-and-tools-did-you-use-jupyter-notebooks-github-the-various-textbooks-we-have-recommended-etc-etc" title="Link to this heading">#</a></h3>
|
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</section>
|
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<section id="if-you-did-not-attend-the-lectures-or-the-lab-sessions-which-resources-did-you-use">
|
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<h3>If you did not attend the lectures or the lab sessions, which resources did you use?<a class="headerlink" href="#if-you-did-not-attend-the-lectures-or-the-lab-sessions-which-resources-did-you-use" title="Link to this heading">#</a></h3>
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</section>
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<section id="any-other-topics-impressions-ideas-etc-you-would-like-to-share-with-us">
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<h3>Any other topics, impressions, ideas etc you would like to share with us?<a class="headerlink" href="#any-other-topics-impressions-ideas-etc-you-would-like-to-share-with-us" title="Link to this heading">#</a></h3>
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<li class="toc-h1 nav-item toc-entry"><a class="reference internal nav-link" href="#">Exercises week 48</a></li>
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<li class="toc-h1 nav-item toc-entry"><a class="reference internal nav-link" href="#overarching-aims-of-the-exercises-this-week">Overarching aims of the exercises this week</a><ul class="visible nav section-nav flex-column">
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#why-did-you-choose-this-course">Why did you choose this course?</a></li>
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#what-was-your-programming-knowledge-before-you-started">What was your programming knowledge before you started?</a></li>
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#how-do-you-judge-your-own-level-of-knowledge-on-machine-learning-before-and-after-this-course">How do you judge your own level of knowledge on machine learning before and after this course?</a></li>
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#did-the-projects-and-the-teaching-material-allow-you-to-deepen-your-insights-about-machine-learning-methods">Did the projects and the teaching material allow you to deepen your insights about Machine Learning methods?</a></li>
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#project-based-teaching-and-active-learning">Project based teaching and active learning</a></li>
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#usefulness-of-the-weekly-exercises">Usefulness of the weekly exercises</a></li>
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#lab-sessions-and-lectures">Lab sessions and lectures</a></li>
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#how-would-you-improve-this-course">How would you improve this course?</a></li>
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#which-is-your-preferred-information-chanel-canvas-discord-mail-or-other">Which is your preferred information chanel, Canvas, Discord, mail or other?</a></li>
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#was-the-weekly-update-with-plans-etc-useful">Was the weekly update with plans etc useful?</a></li>
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#was-it-easy-to-access-the-course-material">Was it easy to access the course material?</a></li>
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#which-resources-and-tools-did-you-use-jupyter-notebooks-github-the-various-textbooks-we-have-recommended-etc-etc">Which resources and tools did you use? Jupyter-notebooks, GitHub, the various textbooks we have recommended, etc etc</a></li>
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#if-you-did-not-attend-the-lectures-or-the-lab-sessions-which-resources-did-you-use">If you did not attend the lectures or the lab sessions, which resources did you use?</a></li>
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#any-other-topics-impressions-ideas-etc-you-would-like-to-share-with-us">Any other topics, impressions, ideas etc you would like to share with us?</a></li>
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