Morten Hjorth-Jensen
239 lines
12 KiB
HTML
239 lines
12 KiB
HTML
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<a class="navbar-brand" href="Project1-bs.html">Project 1 on Machine Learning, deadline October 6 (midnight), 2025</a>
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<!-- navigation toc: --> <li><a href="#preamble-note-on-writing-reports-using-reference-material-ai-and-other-tools" style="font-size: 80%;"><b>Preamble: Note on writing reports, using reference material, AI and other tools</b></a></li>
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<!-- navigation toc: --> <li><a href="._Project1-bs001.html#regression-analysis-and-resampling-methods" style="font-size: 80%;"><b>Regression analysis and resampling methods</b></a></li>
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<!-- navigation toc: --> <li><a href="._Project1-bs001.html#part-a-ordinary-least-square-ols-for-the-runge-function" style="font-size: 80%;"> Part a : Ordinary Least Square (OLS) for the Runge function</a></li>
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<!-- navigation toc: --> <li><a href="._Project1-bs001.html#part-b-adding-ridge-regression-for-the-runge-function" style="font-size: 80%;"> Part b: Adding Ridge regression for the Runge function</a></li>
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<!-- navigation toc: --> <li><a href="._Project1-bs001.html#part-c-writing-your-own-gradient-descent-code" style="font-size: 80%;"> Part c: Writing your own gradient descent code</a></li>
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<!-- navigation toc: --> <li><a href="._Project1-bs001.html#part-d-including-momentum-and-more-advanced-ways-to-update-the-learning-the-rate" style="font-size: 80%;"> Part d: Including momentum and more advanced ways to update the learning the rate</a></li>
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<!-- navigation toc: --> <li><a href="._Project1-bs001.html#part-e-writing-our-own-code-for-lasso-regression" style="font-size: 80%;"> Part e: Writing our own code for Lasso regression</a></li>
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<!-- navigation toc: --> <li><a href="._Project1-bs001.html#part-f-stochastic-gradient-descent" style="font-size: 80%;"> Part f: Stochastic gradient descent</a></li>
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<!-- navigation toc: --> <li><a href="._Project1-bs001.html#part-g-bias-variance-trade-off-and-resampling-techniques" style="font-size: 80%;"> Part g: Bias-variance trade-off and resampling techniques</a></li>
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<!-- navigation toc: --> <li><a href="._Project1-bs001.html#part-h-cross-validation-as-resampling-techniques-adding-more-complexity" style="font-size: 80%;"> Part h): Cross-validation as resampling techniques, adding more complexity</a></li>
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<!-- navigation toc: --> <li><a href="._Project1-bs001.html#background-literature" style="font-size: 80%;"><b>Background literature</b></a></li>
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<!-- navigation toc: --> <li><a href="._Project1-bs001.html#introduction-to-numerical-projects" style="font-size: 80%;"><b>Introduction to numerical projects</b></a></li>
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<!-- navigation toc: --> <li><a href="._Project1-bs001.html#format-for-electronic-delivery-of-report-and-programs" style="font-size: 80%;"><b>Format for electronic delivery of report and programs</b></a></li>
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<!-- navigation toc: --> <li><a href="._Project1-bs001.html#software-and-needed-installations" style="font-size: 80%;"><b>Software and needed installations</b></a></li>
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<p> </p><p> </p><p> </p> <!-- add vertical space -->
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<a name="part0000"></a>
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<!-- ------------------- main content ---------------------- -->
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<div class="jumbotron">
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<center>
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<h1>Project 1 on Machine Learning, deadline October 6 (midnight), 2025</h1>
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</center> <!-- document title -->
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<!-- author(s): Data Analysis and Machine Learning FYS-STK3155/FYS4155 -->
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<center>
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<b>Data Analysis and Machine Learning FYS-STK3155/FYS4155</b>
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</center>
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<!-- institution -->
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<center>
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<b>University of Oslo, Norway</b>
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<br>
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<center>
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<h4>September 2</h4>
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</center> <!-- date -->
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<br>
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</div> <!-- end jumbotron -->
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<h2 id="preamble-note-on-writing-reports-using-reference-material-ai-and-other-tools" class="anchor">Preamble: Note on writing reports, using reference material, AI and other tools </h2>
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<p>We want you to answer the three different projects by handing in
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reports written like a standard scientific/technical report. The
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links at
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<a href="https://github.com/CompPhysics/MachineLearning/tree/master/doc/Projects" target="_self"><tt>https://github.com/CompPhysics/MachineLearning/tree/master/doc/Projects</tt></a>
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contain more information. There you can find examples of previous
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reports, the projects themselves, how we rade reports etc. How to
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write reports will also be discussed during the various lab
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sessions. Please do ask us if you are in doubt.
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</p>
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<p>When using codes and material from other sources, you should refer to
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these in the bibliography of your report, indicating wherefrom you for
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example got the code, whether this is from the lecture notes,
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softwares like Scikit-Learn, TensorFlow, PyTorch or other sources. These sources
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should always be cited correctly. How to cite some
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of the libraries is often indicated from their corresponding GitHub
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sites or websites, see for example how to cite Scikit-Learn at
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<a href="https://scikit-learn.org/dev/about.html" target="_self"><tt>https://scikit-learn.org/dev/about.html</tt></a>.
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</p>
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<p>We enocurage you to use tools like
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<a href="https://openai.com/chatgpt/" target="_self">ChatGPT</a> or similar in writing the report. If you use for example ChatGPT,
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please do cite it properly and include (if possible) your questions and answers as an addition to the report. This can
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be uploaded to for example your website, GitHub/GitLab or similar as supplemental material.
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</p>
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<p>If you would like to study other data sets, feel free to propose other
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sets. What we have proposed here are mere suggestions from our
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side. If you opt for another data set, consider using a set which has
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been studied in the scientific literature. This makes it easier for
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you to compare and analyze your results. Comparing with existing
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results from the scientific literature is also an essential element of
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the scientific discussion. The University of California at Irvine
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with its Machine Learning repository at
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<a href="https://archive.ics.uci.edu/ml/index.php" target="_self"><tt>https://archive.ics.uci.edu/ml/index.php</tt></a> is an excellent site to
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look up for examples and
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inspiration. <a href="https://www.kaggle.com/" target="_self">Kaggle.com</a> is an equally
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interesting site. Feel free to explore these sites. When selecting
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other data sets, make sure these are sets used for regression problems
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(not classification).
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</p>
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<p>
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<li class="active"><a href="._Project1-bs000.html">1</a></li>
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<li><a href="._Project1-bs001.html">2</a></li>
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