update lecture notes
This commit is contained in:
Morten Hjorth-Jensen
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<a class="reference internal nav-link" href="#weekly-schedule">
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Weekly Schedule
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-34-august-22-26">
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Week 34 August 22-26
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-35-august-29-september-2">
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Week 35 August 29-September 2
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</a>
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-36-september-5-9">
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Week 36 September 5-9
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-37-september-12-16">
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Week 37 September 12-16
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</a>
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</li>
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-38-september-19-23">
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Week 38 September 19-23
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</a>
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</li>
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-39-september-26-30">
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Week 39 September 26-30
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</a>
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</li>
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-40-october-3-7">
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Week 40 October 3-7
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</a>
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</li>
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-41-october-10-14">
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Week 41 October 10-14
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</a>
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</li>
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-42-october-17-21">
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Week 42 October 17-21
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</a>
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</li>
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-43-october-24-28">
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Week 43 October 24-28
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</a>
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</li>
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-44-october-31-november-4">
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Week 44 October 31-November 4
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</a>
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</li>
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-45-november-7-11">
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Week 45 November 7-11
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</a>
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</li>
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-46-november-14-18">
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Week 46 November 14-18
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</a>
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</li>
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-47-november-21-25">
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Week 47 November 21-25
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</a>
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</li>
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</ul>
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</li>
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</ul>
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@@ -411,78 +339,6 @@ const thebe_selector_output = ".output, .cell_output"
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<a class="reference internal nav-link" href="#weekly-schedule">
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Weekly Schedule
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</a>
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<ul class="nav section-nav flex-column">
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-34-august-22-26">
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Week 34 August 22-26
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</a>
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</li>
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-35-august-29-september-2">
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Week 35 August 29-September 2
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</a>
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</li>
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-36-september-5-9">
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Week 36 September 5-9
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</a>
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</li>
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-37-september-12-16">
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Week 37 September 12-16
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</a>
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</li>
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-38-september-19-23">
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Week 38 September 19-23
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</a>
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</li>
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-39-september-26-30">
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Week 39 September 26-30
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</a>
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</li>
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-40-october-3-7">
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Week 40 October 3-7
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</a>
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</li>
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-41-october-10-14">
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Week 41 October 10-14
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</a>
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</li>
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-42-october-17-21">
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Week 42 October 17-21
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</a>
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</li>
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-43-october-24-28">
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Week 43 October 24-28
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</a>
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</li>
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-44-october-31-november-4">
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Week 44 October 31-November 4
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</a>
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</li>
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-45-november-7-11">
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Week 45 November 7-11
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</a>
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</li>
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-46-november-14-18">
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Week 46 November 14-18
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</a>
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</li>
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<li class="toc-h3 nav-item toc-entry">
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<a class="reference internal nav-link" href="#week-47-november-21-25">
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Week 47 November 21-25
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</a>
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</li>
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</ul>
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</li>
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</ul>
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@@ -515,322 +371,6 @@ const thebe_selector_output = ".output, .cell_output"
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<li><p>HTF: Hastie, Tibshirani, and Friedman, The Elements of Statistical Learning</p></li>
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<li><p>AG: Aurelien Geron, Hands‑On Machine Learning with Scikit‑Learn and TensorFlow</p></li>
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</ul>
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<div class="section" id="week-34-august-22-26">
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<h3>Week 34 August 22-26<a class="headerlink" href="#week-34-august-22-26" title="Permalink to this headline">¶</a></h3>
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<ul class="simple">
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<li><p>Lab Wednesday: Introduction to software and repetition of Python Programming</p></li>
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<li><p>Lecture Thursday: Introduction to the course, what is Machine Learning and introduction to Linear Regression.</p></li>
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<li><p>Video of Lecture August 25, 2022 at <a class="reference external" href="https://youtu.be/KL0m3-yhd5w">https://youtu.be/KL0m3-yhd5w</a></p></li>
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<li><p>Lecture Friday: Basics of Linear Regression</p></li>
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<li><p>Video of Lecture August 26, 2022 at <a class="reference external" href="https://youtu.be/ne_xCL2ctM0">https://youtu.be/ne_xCL2ctM0</a></p></li>
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<li><p>Reading recommendations:</p>
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<ul>
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<li><p>Refresh linear algebra, GBC chapters 1 and 2.</p></li>
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<li><p>CMB sections 1.1 and 3.1.</p></li>
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<li><p>HTF chapters 2 and 3.</p></li>
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<li><p>See lecture notes for week 34 at <a class="reference external" href="https://compphysics.github.io/MachineLearning/doc/web/course.html">https://compphysics.github.io/MachineLearning/doc/web/course.html</a></p></li>
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</ul>
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</li>
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</ul>
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</div>
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<div class="section" id="week-35-august-29-september-2">
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<h3>Week 35 August 29-September 2<a class="headerlink" href="#week-35-august-29-september-2" title="Permalink to this headline">¶</a></h3>
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<ul class="simple">
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<li><p>Lab Wednesday: Work on exercises 1-5 for week 35</p></li>
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<li><p>Thursday: Review of ordinary Least Squares with applications, reminder on statistics and start discussion of Ridge Regression and Singular Value Decomposition</p></li>
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<li><p>Video of lecture Thursday at <a class="reference external" href="https://youtu.be/jYdg2xzKa5E">https://youtu.be/jYdg2xzKa5E</a></p></li>
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<li><p>Friday: Discussion of Ridge and Lasso Regression and links with Singular Value Decomposition</p></li>
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<li><p>Video of lecture Friday at <a class="reference external" href="https://youtu.be/07e-SUYRzM0">https://youtu.be/07e-SUYRzM0</a></p></li>
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<li><p>Reading recommendations:</p>
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<ul>
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<li><p>See lecture notes for week 35 at <a class="reference external" href="https://compphysics.github.io/MachineLearning/doc/web/course.html">https://compphysics.github.io/MachineLearning/doc/web/course.html</a>.</p></li>
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<li><p>For a review on statistics see jupyter-book <a class="reference external" href="https://compphysics.github.io/MachineLearning/doc/LectureNotes/_build/html/statistics.html">https://compphysics.github.io/MachineLearning/doc/LectureNotes/_build/html/statistics.html</a>, the most relevant parts are covered by sections 1.1.1-1.1.5</p></li>
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<li><p>HTF chapter 3. GBC chapters 1 and and sections 3.1-3.11 and 5.1</p></li>
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<li><p>CMB sections 1.1 and 3.1</p></li>
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<li><p>A good review on statistics is given by Murphy’s text, chapter 2, see <a class="reference external" href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/Textbooks/MachineLearningMurphy.pdf">https://github.com/CompPhysics/MachineLearning/blob/master/doc/Textbooks/MachineLearningMurphy.pdf</a></p></li>
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</ul>
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</li>
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</ul>
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</div>
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<div class="section" id="week-36-september-5-9">
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<h3>Week 36 September 5-9<a class="headerlink" href="#week-36-september-5-9" title="Permalink to this headline">¶</a></h3>
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<ul class="simple">
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<li><p>Lab Wednesday: Exercises 1 and 2 from week 36</p></li>
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<li><p>Lecture Thursday: Summary from last week on SVD, more on Statistics, probability theory and linear regression</p></li>
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<li><p>Video of Lecture at <a class="reference external" href="https://youtu.be/qn_BAVhMD8U">https://youtu.be/qn_BAVhMD8U</a></p></li>
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<li><p>Friday: Linear Regression and more links with Statistics, Resampling methods and presentation of first project.</p></li>
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<li><p>Video of Lecture at <a class="reference external" href="https://youtu.be/_CPGg0JYH8M">https://youtu.be/_CPGg0JYH8M</a></p></li>
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<li><p>Reading recommendations:</p>
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<ul>
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<li><p>Lectures on Regression for week 36 at <a class="reference external" href="https://compphysics.github.io/MachineLearning/doc/web/course.html">https://compphysics.github.io/MachineLearning/doc/web/course.html</a>.</p></li>
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<li><p>Bishop 1.1, 1.2, 2.1, 2.2, 2.3 and 3.1</p></li>
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<li><p>Hastie et al chapter 3</p></li>
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</ul>
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</li>
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</ul>
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</div>
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<div class="section" id="week-37-september-12-16">
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<h3>Week 37 September 12-16<a class="headerlink" href="#week-37-september-12-16" title="Permalink to this headline">¶</a></h3>
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<ul class="simple">
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<li><p>Lab Wednesday: Work on Project 1</p></li>
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<li><p>Lecture Thursday: Resampling methods, cross-validation and Bootstrap</p>
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<ul>
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<li><p>Thursday September: Summary of Ridge and Lasso with examples and start resampling techniques</p>
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<ul>
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<li><p>Video of Lecture at <a class="reference external" href="https://youtu.be/YVQGvcsovpw">https://youtu.be/YVQGvcsovpw</a></p></li>
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</ul>
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</li>
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</ul>
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</li>
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<li><p>Lecture Friday: More on Resampling methods and summary of linear regression</p>
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<ul>
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<li><p>Video of Lecture at <a class="reference external" href="https://youtu.be/rbaHRF-7bsQ">https://youtu.be/rbaHRF-7bsQ</a></p></li>
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</ul>
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</li>
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<li><p>Reading recommendations:</p>
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<ul>
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<li><p>Lectures on Resampling methods for week 37 at <a class="reference external" href="https://compphysics.github.io/MachineLearning/doc/web/course.html">https://compphysics.github.io/MachineLearning/doc/web/course.html</a>.</p></li>
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<li><p>Bishop 1.3 (cross-validation) and 3.2 (bias-variance tradeoff)</p></li>
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<li><p>Hastie et al Chapter 7, here we recommend 7.1-7.5 and 7.10 (cross-validation) and 7.11 (bootstrap)</p></li>
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<li><p>Goodfellow et al discuss some of these topics in sections 5.2-5.5.</p></li>
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</ul>
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</li>
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</ul>
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</div>
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<div class="section" id="week-38-september-19-23">
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<h3>Week 38 September 19-23<a class="headerlink" href="#week-38-september-19-23" title="Permalink to this headline">¶</a></h3>
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<ul class="simple">
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<li><p>Lab Wednesday: Work on Project 1</p></li>
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<li><p>Lecture Thursday: Classification problems and Logistic Regression, from binary cases to several categories and gradient optmization</p>
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<ul>
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<li><p>Video of Lecture at <a class="reference external" href="https://youtu.be/sdt_BFla8uA">https://youtu.be/sdt_BFla8uA</a></p></li>
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</ul>
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</li>
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<li><p>Lecture Friday: Logistic Regression and gradient optimization</p>
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<ul>
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<li><p>Video of Lecture at <a class="reference external" href="https://youtu.be/7OdqoLOphTA">https://youtu.be/7OdqoLOphTA</a></p></li>
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</ul>
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</li>
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<li><p>Reading recommendations:</p>
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<ul>
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<li><p>See lecture notes for week 38 at <a class="reference external" href="https://compphysics.github.io/MachineLearning/doc/web/course.html">https://compphysics.github.io/MachineLearning/doc/web/course.html</a>.</p></li>
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<li><p>Bishop 4.1, 4.2 and 4.3. Not all the material is relevant or will be covered. Section 4.3 is the most relevant, but 4.1 and 4.2 give interesting background readings for logistic regression</p></li>
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<li><p>Hastie et al 4.1, 4.2 and 4.3 on logistic regression</p></li>
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<li><p>For a good discussion on gradient methods, see Goodfellow et al section 4.3-4.5 and chapter 8. We will come back to the latter chapter in our discussion of Neural networks as well.</p></li>
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</ul>
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</li>
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</ul>
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</div>
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<div class="section" id="week-39-september-26-30">
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<h3>Week 39 September 26-30<a class="headerlink" href="#week-39-september-26-30" title="Permalink to this headline">¶</a></h3>
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<ul class="simple">
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<li><p>Lab Wednesday: Work on Project 1</p></li>
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<li><p>Lecture Thursday: * Thursday: Repetition of Logistic regression equations and classification problems and discussion of Gradient methods. Examples on how to implement Logistic Regression and discussion of stochastic gradient descent</p>
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<ul>
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<li><p>Video of lecture at <a class="reference external" href="https://youtu.be/rDBj50Lv3Go">https://youtu.be/rDBj50Lv3Go</a></p></li>
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</ul>
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</li>
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</ul>
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<ul class="simple">
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<li><p>Friday: Stochastic Gradient descent with examples and automatic differentiation</p>
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<ul>
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<li><p>Video of lecture at <a class="reference external" href="https://youtu.be/OH6I_oscwPc">https://youtu.be/OH6I_oscwPc</a></p></li>
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</ul>
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</li>
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<li><p>Reading recommendations:</p>
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<ul>
|
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<li><p>See lecture notes for week 39 at <a class="reference external" href="https://compphysics.github.io/MachineLearning/doc/web/course.html">https://compphysics.github.io/MachineLearning/doc/web/course.html</a>.</p></li>
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<li><p>For a good discussion on gradient methods, see Goodfellow et al section 4.3-4.5 and chapter 8. We will come back to the latter chapter in our discussion of Neural networks as well.</p></li>
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</ul>
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</li>
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</ul>
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</div>
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<div class="section" id="week-40-october-3-7">
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<h3>Week 40 October 3-7<a class="headerlink" href="#week-40-october-3-7" title="Permalink to this headline">¶</a></h3>
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<ul class="simple">
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<li><p>Lab Wednesday: Wrap up project 1</p></li>
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<li><p>Lecture Thursday: Stochastic gradient descent, automatic differentiation and start discussion of feed-forward Neural Network code for regression and classification</p>
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<ul>
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<li><p>Video of Lecture at <a class="reference external" href="https://youtu.be/sCHiGSoG2lE">https://youtu.be/sCHiGSoG2lE</a></p></li>
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</ul>
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</li>
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<li><p>Lecture Friday: Deep Learning and Neural Networks: the back propagation algorithm</p>
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<ul>
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<li><p>Video of Lecture at <a class="reference external" href="https://youtu.be/hDTtA7PRRfI">https://youtu.be/hDTtA7PRRfI</a></p></li>
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</ul>
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</li>
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<li><p>Reading recommendations:</p>
|
||||
<ul>
|
||||
<li><p>See lecture notes for week 40 at <a class="reference external" href="https://compphysics.github.io/MachineLearning/doc/web/course.html">https://compphysics.github.io/MachineLearning/doc/web/course.html</a>.</p></li>
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<li><p>For neural networks we recommend Goodfellow et al chapters 6 and 7 and Bishop 5.1-5.4</p></li>
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<li><p>For stochastic gradient descent we recommend Goodfellow et al chapter 8</p></li>
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</ul>
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</li>
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</ul>
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</div>
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<div class="section" id="week-41-october-10-14">
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<h3>Week 41 October 10-14<a class="headerlink" href="#week-41-october-10-14" title="Permalink to this headline">¶</a></h3>
|
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<ul class="simple">
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<li><p>Lab Wednesday: Work on project 2</p></li>
|
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<li><p>Lecture Thursday: Deep learning and Neural Networks, developing a code for Neural Networks</p>
|
||||
<ul>
|
||||
<li><p>Video of Lecture at <a class="reference external" href="https://youtu.be/yzbxJI6LgL0">https://youtu.be/yzbxJI6LgL0</a></p></li>
|
||||
</ul>
|
||||
</li>
|
||||
<li><p>Lecture Friday: Developing a neural network code</p>
|
||||
<ul>
|
||||
<li><p>Video of Lecture at <a class="reference external" href="https://youtu.be/CPj4mh7M9no">https://youtu.be/CPj4mh7M9no</a></p></li>
|
||||
</ul>
|
||||
</li>
|
||||
<li><p>Reading recommendations:</p>
|
||||
<ul>
|
||||
<li><p>See lecture notes for week 41 at <a class="reference external" href="https://compphysics.github.io/MachineLearning/doc/web/course.html">https://compphysics.github.io/MachineLearning/doc/web/course.html</a>.</p></li>
|
||||
<li><p>For neural networks we recommend Goodfellow et al chapters 6 and 7. For CNNs, see Goodfellow et al chapter 9. chapter 11 and 12 on practicalities and applications</p></li>
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
<div class="section" id="week-42-october-17-21">
|
||||
<h3>Week 42 October 17-21<a class="headerlink" href="#week-42-october-17-21" title="Permalink to this headline">¶</a></h3>
|
||||
<ul class="simple">
|
||||
<li><p>Lab Wednesday: Work on project 2</p></li>
|
||||
<li><p>Lecture Thursday: Discussion of Neural Network calculations and tensorflow. Solving differential equations with neural networks</p>
|
||||
<ul>
|
||||
<li><p>Video of Lecture at <a class="reference external" href="https://youtu.be/MdYT6uwOkT0">https://youtu.be/MdYT6uwOkT0</a></p></li>
|
||||
</ul>
|
||||
</li>
|
||||
<li><p>Lecture Friday: Convolutional Neural Networks and classification problems</p>
|
||||
<ul>
|
||||
<li><p>Video of Lecture at <a class="reference external" href="https://youtu.be/3bDkrB-E7cU">https://youtu.be/3bDkrB-E7cU</a></p></li>
|
||||
</ul>
|
||||
</li>
|
||||
<li><p>Reading recommendations:</p>
|
||||
<ul>
|
||||
<li><p>See lecture notes for week 42 at <a class="reference external" href="https://compphysics.github.io/MachineLearning/doc/web/course.html">https://compphysics.github.io/MachineLearning/doc/web/course.html</a>.</p></li>
|
||||
<li><p>For neural networks we recommend Goodfellow et al chapters 6 and 7. For CNNs, see Goodfellow et al chapter 9. See also chapter 11 and 12 on practicalities and applications</p></li>
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
<div class="section" id="week-43-october-24-28">
|
||||
<h3>Week 43 October 24-28<a class="headerlink" href="#week-43-october-24-28" title="Permalink to this headline">¶</a></h3>
|
||||
<ul class="simple">
|
||||
<li><p>Lab Wednesday: Work on project 2</p></li>
|
||||
<li><p>Lecture Thursday: Recurrent Neural Networks</p>
|
||||
<ul>
|
||||
<li><p>Video of Lecture at <a class="reference external" href="https://youtu.be/Hm6Ay5DS6o0">https://youtu.be/Hm6Ay5DS6o0</a></p></li>
|
||||
</ul>
|
||||
</li>
|
||||
<li><p>Lecture Friday: Recurrent Neural Networks and time series and principal component analysis (PCA)</p>
|
||||
<ul>
|
||||
<li><p>Video of Lecture at <a class="reference external" href="https://youtu.be/JHfgQ77fpqs">https://youtu.be/JHfgQ77fpqs</a></p></li>
|
||||
</ul>
|
||||
</li>
|
||||
<li><p>Reading recommendations:</p>
|
||||
<ul>
|
||||
<li><p>See lecture notes for week 43 at <a class="reference external" href="https://compphysics.github.io/MachineLearning/doc/web/course.html">https://compphysics.github.io/MachineLearning/doc/web/course.html</a>.</p></li>
|
||||
<li><p>For RNNs, see Goodfellow et al chapter 10 and discussions in chapter 11 and 12 on practicalities and applications</p></li>
|
||||
<li><p>For PCA, see lecture notes chapter 11 and Geron’s text chapter 8</p></li>
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
<div class="section" id="week-44-october-31-november-4">
|
||||
<h3>Week 44 October 31-November 4<a class="headerlink" href="#week-44-october-31-november-4" title="Permalink to this headline">¶</a></h3>
|
||||
<ul class="simple">
|
||||
<li><p>Lab Wednesday: Work on project 2</p></li>
|
||||
<li><p>Lecture Thursday: Decision trees, basic algorithms for classification and regression</p>
|
||||
<ul>
|
||||
<li><p>Video of Lecture at <a class="reference external" href="https://youtu.be/7jexGH5SOOE">https://youtu.be/7jexGH5SOOE</a></p></li>
|
||||
</ul>
|
||||
</li>
|
||||
<li><p>Lecture Friday: From trees to forests and ensemble methods</p>
|
||||
<ul>
|
||||
<li><p>Video of Lecture at <a class="reference external" href="https://youtu.be/9QcU8VcXxRU">https://youtu.be/9QcU8VcXxRU</a></p></li>
|
||||
</ul>
|
||||
</li>
|
||||
<li><p>Reading recommendations:</p>
|
||||
<ul>
|
||||
<li><p>See lecture notes for week 44 at <a class="reference external" href="https://compphysics.github.io/MachineLearning/doc/web/course.html">https://compphysics.github.io/MachineLearning/doc/web/course.html</a>.</p></li>
|
||||
<li><p>Hastie et al sections 9.1 and 9.2. Geron’s text chapter 6 (Decision trees)</p></li>
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
<div class="section" id="week-45-november-7-11">
|
||||
<h3>Week 45 November 7-11<a class="headerlink" href="#week-45-november-7-11" title="Permalink to this headline">¶</a></h3>
|
||||
<ul class="simple">
|
||||
<li><p>Lab Wednesday: Work on project 2, project 3 available November 11.</p></li>
|
||||
<li><p>Lecture Thursday: Ensemble methods, bagging and random forests, boosting.</p>
|
||||
<ul>
|
||||
<li><p>Video of Lecture at <a class="reference external" href="https://youtu.be/mK48PfCxgYk">https://youtu.be/mK48PfCxgYk</a></p></li>
|
||||
</ul>
|
||||
</li>
|
||||
<li><p>Lecture Friday: Adaptive boosting and gradient boosting, summary of decision trees and ensemble methods</p>
|
||||
<ul>
|
||||
<li><p>Video of Lecture at <a class="reference external" href="https://youtu.be/v8eJBFeZKuI">https://youtu.be/v8eJBFeZKuI</a></p></li>
|
||||
</ul>
|
||||
</li>
|
||||
<li><p>Reading recommendations:</p>
|
||||
<ul>
|
||||
<li><p>See lecture notes for week 45 at <a class="reference external" href="https://compphysics.github.io/MachineLearning/doc/web/course.html">https://compphysics.github.io/MachineLearning/doc/web/course.html</a>.</p></li>
|
||||
<li><p>Hastie et al chapter 10 and Geron chapters 5 and 6</p></li>
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
<div class="section" id="week-46-november-14-18">
|
||||
<h3>Week 46 November 14-18<a class="headerlink" href="#week-46-november-14-18" title="Permalink to this headline">¶</a></h3>
|
||||
<ul class="simple">
|
||||
<li><p>Lab Wednesday: Work on project 3</p></li>
|
||||
<li><p>Lecture Thursday: Support Vector machines</p>
|
||||
<ul>
|
||||
<li><p>Video of Lecture at <a class="reference external" href="https://youtu.be/F3CkH-opbdY">https://youtu.be/F3CkH-opbdY</a></p></li>
|
||||
</ul>
|
||||
</li>
|
||||
<li><p>Lecture Friday: Workshop on project 3</p>
|
||||
<ul>
|
||||
<li><p>Video of Lecture at <a class="reference external" href="https://youtu.be/BbupEEvMXtg">https://youtu.be/BbupEEvMXtg</a></p></li>
|
||||
</ul>
|
||||
</li>
|
||||
<li><p>Reading recommendations:</p>
|
||||
<ul>
|
||||
<li><p>See lecture notes for week 46 at <a class="reference external" href="https://compphysics.github.io/MachineLearning/doc/web/course.html">https://compphysics.github.io/MachineLearning/doc/web/course.html</a>.</p></li>
|
||||
<li><p>Hastie et al chapter 12</p></li>
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
<div class="section" id="week-47-november-21-25">
|
||||
<h3>Week 47 November 21-25<a class="headerlink" href="#week-47-november-21-25" title="Permalink to this headline">¶</a></h3>
|
||||
<ul class="simple">
|
||||
<li><p>Lab Wednesday: Work on project 3</p></li>
|
||||
<li><p>Lecture Thursday: Dimensionality reduction and unsupervised learning: Principal Component analysis (PCA) and clustering</p>
|
||||
<ul>
|
||||
<li><p>Video of Lecture <a class="reference external" href="https://youtu.be/VJIsEQM2lCI">https://youtu.be/VJIsEQM2lCI</a></p></li>
|
||||
</ul>
|
||||
</li>
|
||||
<li><p>Lecture Friday: PCA and clustering and Summary of Course</p>
|
||||
<ul>
|
||||
<li><p>Video of Lecture <a class="reference external" href="https://youtu.be/olXksEL3P4A">https://youtu.be/olXksEL3P4A</a></p></li>
|
||||
</ul>
|
||||
</li>
|
||||
<li><p>Reading recommendations:</p>
|
||||
<ul>
|
||||
<li><p>See lecture notes for week 47 at <a class="reference external" href="https://compphysics.github.io/MachineLearning/doc/web/course.html">https://compphysics.github.io/MachineLearning/doc/web/course.html</a>.</p></li>
|
||||
<li><p>Geron’s chapter 9 on PCA</p></li>
|
||||
<li><p>Hastie et al Chapter 13 (sections 13.1-13.2 are the most relevant ones)</p></li>
|
||||
</ul>
|
||||
</li>
|
||||
<li><p>Excellent videos:</p>
|
||||
<ul>
|
||||
<li><p>We recommend highly the video on PCA by Brunton and Kutz at <a class="reference external" href="http://www.databookuw.com/page-2/page-4/">http://www.databookuw.com/page-2/page-4/</a>, see in particular the video of section 1.5.</p></li>
|
||||
<li><p>And another good video on PCA is at <a class="reference external" href="https://www.youtube.com/watch?v=FgakZw6K1QQ">https://www.youtube.com/watch?v=FgakZw6K1QQ</a></p></li>
|
||||
<li><p>k-means clustering video at <a class="reference external" href="https://www.youtube.com/watch?v=4b5d3muPQmA">https://www.youtube.com/watch?v=4b5d3muPQmA</a></p></li>
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
|
||||
Reference in New Issue
Block a user