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update week 35

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Morten Hjorth-Jensen
2023-07-08 20:49:55 +02:00
parent 13cfa56fe4
commit 14d8d549d3
9 changed files with 454 additions and 444 deletions
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doc/pub/week35/html/._week35-bs000.html
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</center>
<br>
<center>
<h4>Jul 5, 2023</h4>
<h4>Jul 8, 2023</h4>
</center> <!-- date -->
<br>
doc/pub/week35/html/._week35-bs001.html
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<h2 id="plans-for-week-35" class="anchor">Plans for week 35 </h2>
<p>The main topics are:</p>
<ol>
<li> Repetition from last week on linear regression</li>
<li> Reminder on statistics with quantities like mean values, variance abd covariance</li>
<li> Discussion of how to prepare data and examples of applications of linear regression</li>
<li> Mathematical interpretations of Linear Regression</li>
<li> Start discussing Ridge and Lasso regression and Singular Value Decomposition</li>
<li> Brief repetition from last week</li>
<li> Reminder on statistics with quantities like mean values, variance and covariance</li>
<li> Discussion on how to prepare data and examples of applications of linear regression</li>
<li> Mathematical interpretations of linear regression</li>
<li> Ridge and Lasso regression and Singular Value Decomposition</li>
</ol>
<h3 id="reading-recommendations" class="anchor">Reading recommendations: </h3>
<ol>
<li> See lecture notes for week 35 at <a href="https://compphysics.github.io/MachineLearning/doc/web/course.html" target="_self"><tt>https://compphysics.github.io/MachineLearning/doc/web/course.html</tt></a></li>
<li> For a review on statistics see jupyter-book <a href="https://compphysics.github.io/MachineLearning/doc/LectureNotes/_build/html/statistics.html" target="_self"><tt>https://compphysics.github.io/MachineLearning/doc/LectureNotes/_build/html/statistics.html</tt></a>, the most relevant parts are covered by sections 1.1.1-1.1.5</li>
doc/pub/week35/html/week35-bs.html
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@@ -400,7 +400,7 @@ MathJax.Hub.Config({
</center>
<br>
<center>
<h4>Jul 5, 2023</h4>
<h4>Jul 8, 2023</h4>
</center> <!-- date -->
<br>
doc/pub/week35/html/week35-reveal.html
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@@ -184,7 +184,7 @@ MathJax.Hub.Config({
</center>
<br>
<center>
<h4>Jul 5, 2023</h4>
<h4>Jul 8, 2023</h4>
</center> <!-- date -->
<br>
@@ -198,15 +198,17 @@ MathJax.Hub.Config({
<h2 id="plans-for-week-35">Plans for week 35 </h2>
<p>The main topics are:</p>
<ol>
<p><li> Repetition from last week on linear regression</li>
<p><li> Reminder on statistics with quantities like mean values, variance abd covariance</li>
<p><li> Discussion of how to prepare data and examples of applications of linear regression</li>
<p><li> Mathematical interpretations of Linear Regression</li>
<p><li> Start discussing Ridge and Lasso regression and Singular Value Decomposition</li>
<p><li> Brief repetition from last week</li>
<p><li> Reminder on statistics with quantities like mean values, variance and covariance</li>
<p><li> Discussion on how to prepare data and examples of applications of linear regression</li>
<p><li> Mathematical interpretations of linear regression</li>
<p><li> Ridge and Lasso regression and Singular Value Decomposition</li>
</ol>
<p>
<h3 id="reading-recommendations">Reading recommendations: </h3>
<ol>
<p><li> See lecture notes for week 35 at <a href="https://compphysics.github.io/MachineLearning/doc/web/course.html" target="_blank"><tt>https://compphysics.github.io/MachineLearning/doc/web/course.html</tt></a></li>
<p><li> For a review on statistics see jupyter-book <a href="https://compphysics.github.io/MachineLearning/doc/LectureNotes/_build/html/statistics.html" target="_blank"><tt>https://compphysics.github.io/MachineLearning/doc/LectureNotes/_build/html/statistics.html</tt></a>, the most relevant parts are covered by sections 1.1.1-1.1.5</li>
doc/pub/week35/html/week35-solarized.html
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@@ -328,7 +328,7 @@ MathJax.Hub.Config({
</center>
<br>
<center>
<h4>Jul 5, 2023</h4>
<h4>Jul 8, 2023</h4>
</center> <!-- date -->
<br>
@@ -336,14 +336,16 @@ MathJax.Hub.Config({
<h2 id="plans-for-week-35">Plans for week 35 </h2>
<p>The main topics are:</p>
<ol>
<li> Repetition from last week on linear regression</li>
<li> Reminder on statistics with quantities like mean values, variance abd covariance</li>
<li> Discussion of how to prepare data and examples of applications of linear regression</li>
<li> Mathematical interpretations of Linear Regression</li>
<li> Start discussing Ridge and Lasso regression and Singular Value Decomposition</li>
<li> Brief repetition from last week</li>
<li> Reminder on statistics with quantities like mean values, variance and covariance</li>
<li> Discussion on how to prepare data and examples of applications of linear regression</li>
<li> Mathematical interpretations of linear regression</li>
<li> Ridge and Lasso regression and Singular Value Decomposition</li>
</ol>
<h3 id="reading-recommendations">Reading recommendations: </h3>
<ol>
<li> See lecture notes for week 35 at <a href="https://compphysics.github.io/MachineLearning/doc/web/course.html" target="_blank"><tt>https://compphysics.github.io/MachineLearning/doc/web/course.html</tt></a></li>
<li> For a review on statistics see jupyter-book <a href="https://compphysics.github.io/MachineLearning/doc/LectureNotes/_build/html/statistics.html" target="_blank"><tt>https://compphysics.github.io/MachineLearning/doc/LectureNotes/_build/html/statistics.html</tt></a>, the most relevant parts are covered by sections 1.1.1-1.1.5</li>
doc/pub/week35/html/week35.html
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@@ -405,7 +405,7 @@ MathJax.Hub.Config({
</center>
<br>
<center>
<h4>Jul 5, 2023</h4>
<h4>Jul 8, 2023</h4>
</center> <!-- date -->
<br>
@@ -413,14 +413,16 @@ MathJax.Hub.Config({
<h2 id="plans-for-week-35">Plans for week 35 </h2>
<p>The main topics are:</p>
<ol>
<li> Repetition from last week on linear regression</li>
<li> Reminder on statistics with quantities like mean values, variance abd covariance</li>
<li> Discussion of how to prepare data and examples of applications of linear regression</li>
<li> Mathematical interpretations of Linear Regression</li>
<li> Start discussing Ridge and Lasso regression and Singular Value Decomposition</li>
<li> Brief repetition from last week</li>
<li> Reminder on statistics with quantities like mean values, variance and covariance</li>
<li> Discussion on how to prepare data and examples of applications of linear regression</li>
<li> Mathematical interpretations of linear regression</li>
<li> Ridge and Lasso regression and Singular Value Decomposition</li>
</ol>
<h3 id="reading-recommendations">Reading recommendations: </h3>
<ol>
<li> See lecture notes for week 35 at <a href="https://compphysics.github.io/MachineLearning/doc/web/course.html" target="_blank"><tt>https://compphysics.github.io/MachineLearning/doc/web/course.html</tt></a></li>
<li> For a review on statistics see jupyter-book <a href="https://compphysics.github.io/MachineLearning/doc/LectureNotes/_build/html/statistics.html" target="_blank"><tt>https://compphysics.github.io/MachineLearning/doc/LectureNotes/_build/html/statistics.html</tt></a>, the most relevant parts are covered by sections 1.1.1-1.1.5</li>
doc/pub/week35/ipynb/ipynb-week35-src.tar.gz
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doc/pub/week35/ipynb/week35.ipynb
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doc/src/week35/week35.do.txt
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@@ -10,13 +10,14 @@ The main topics are:
o Brief repetition from last week
o Reminder on statistics with quantities like mean values, variance and covariance
o Discussion of how to prepare data and examples of applications of linear regression
o Mathematical interpretations of Linear Regression
o Discussion on how to prepare data and examples of applications of linear regression
o Mathematical interpretations of linear regression
o Ridge and Lasso regression and Singular Value Decomposition
=== Reading recommendations: ===
o See lecture notes for week 35 at URL:"https://compphysics.github.io/MachineLearning/doc/web/course.html"
o For a review on statistics see jupyter-book URL:"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
o HTF chapter 3. GBC chapters 1 and and sections 3.1-3.11 and 5.1