updated schedule
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Morten Hjorth-Jensen
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@@ -36,23 +36,24 @@ For the reading assignments we use the following abbreviations:
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- See lecture notes for week 34 at https://compphysics.github.io/MachineLearning/doc/web/course.html
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### Week 35 August 29-September 2
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- Lab Wednesday: Work on exercises 1-3 for week 35
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- Thursday: Review of ordinary Least Squares with applications and discussion of Ridge Regression and Singular Value Decomposition
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- Lab Wednesday: Work on exercises 1-5 for week 35
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- Thursday: Review of ordinary Least Squares with applications, reminder on statistics and start discussion of Ridge Regression and Singular Value Decomposition
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- Video of lecture Thursday at
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- Friday: Analysis of Ridge and Lasso Regression and links with Singular Value Decomposition
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- Friday: Discussion of Ridge and Lasso Regression and links with Singular Value Decomposition
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- Video of lecture Friday at
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- Reading recommendations:
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- See lecture notes for week 35 at https://compphysics.github.io/MachineLearning/doc/web/course.html.
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- For a review on statistics see jupyter-book https://compphysics.github.io/MachineLearning/doc/LectureNotes/_build/html/statistics.html, the most relevant parts are covered by sections 1.1.1-1.1.5
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- HTF chapter 3. GBC chapters 1 and and sections 3.1-3.11 and 5.1
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- CMB sections 1.1 and 3.1
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- A good review on statistics is given by Murphy's text, chapter 2, see https://github.com/CompPhysics/MachineLearning/blob/master/doc/Textbooks/MachineLearningMurphy.pdf
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### Week 36 September 5-9
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- Lab Wednesday: Exercises 1 and 2 from week 36
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- Lecture Thursday: Summary from last week on SVD, Statistics, probability theory and linear regression
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- Lecture Thursday: Summary from last week on SVD, more on Statistics, probability theory and linear regression
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- Video of Lecture
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- Friday: Linear Regression and links with Statistics, Resampling methods and presentation of first project.
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- Friday: Linear Regression and more links with Statistics, Resampling methods and presentation of first project.
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- Video of Lecture
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- Reading recommendations:
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@@ -533,16 +533,18 @@ const thebe_selector_output = ".output, .cell_output"
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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 1-3 for week 35</p></li>
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<li><p>Thursday: Review of ordinary Least Squares with applications and discussion of Ridge Regression and Singular Value Decomposition</p></li>
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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</p></li>
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<li><p>Friday: Analysis of Ridge and Lasso Regression and links with Singular Value Decomposition</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</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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@@ -551,9 +553,9 @@ const thebe_selector_output = ".output, .cell_output"
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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, Statistics, probability theory and linear regression</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</p></li>
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<li><p>Friday: Linear Regression and links with Statistics, Resampling methods and presentation of first project.</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</p></li>
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<li><p>Reading recommendations:</p>
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<ul>
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