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update week 47

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Morten Hjorth-Jensen
2022-11-21 12:34:30 +01:00
parent 612224b2f8
commit 5973d2b30f
10 changed files with 9904 additions and 898 deletions
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doc/Textbooks/elementsstat.pdf
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doc/pub/week47/html/._week47-bs000.html
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@@ -429,7 +429,7 @@ MathJax.Hub.Config({
</center>
<br>
<center>
<h4>Nov 20, 2022</h4>
<h4>Nov 21, 2022</h4>
</center> <!-- date -->
<br>
doc/pub/week47/html/._week47-bs001.html
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<h2 id="overview-of-week-47" class="anchor">Overview of week 47 </h2>
<ul>
<li> <b>Thursday</b>: Support Vector Machines, classification and regression.</li>
<li> <b>Friday</b>: Support Vector Machines and Summary of Course</li>
<li> <b>Thursday</b>: Dimensionality reduction and unsupervised learning: Principal Component analysis (PCA) and clustering</li>
<li> <b>Friday</b>: PCA and clustering and Summary of Course</li>
</ul>
<b>Excellent video</b>:
<ol>
<li> We recommend highly the video on PCA by <a href="http://www.databookuw.com/page-2/page-4/" target="_self">Brunton and Kutz</a>, see in particular the video of section 1.5. Repeating about the singular value discussion is also very useful as we will use this material as background.</li>
<li> <a href="https://www.youtube.com/watch?v=FgakZw6K1QQ" target="_self">And another good video on PCA</a></li>
<li> <a href="https://www.youtube.com/watch?v=4b5d3muPQmA" target="_self">k-means clustering video</a></li>
</ol>
<p>_Reading recommendations:</p>
<ol>
<li> Geron's chapter 5.</li>
<li> Hastie et al Chapter 12 (sections 12.1-12.3 are the most relevant ones)</li>
<li> Bishop chapter 7, with sections 7.1 and 7.2 as the essential ones</li>
<li> Geron's chapter 9 on PCA</li>
<li> Hastie et al Chapter 13 (sections 13.1-13.2 are the most relevant ones)</li>
</ol>
<p>
<!-- navigation buttons at the bottom of the page -->
doc/pub/week47/html/week47-bs.html
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@@ -429,7 +429,7 @@ MathJax.Hub.Config({
</center>
<br>
<center>
<h4>Nov 20, 2022</h4>
<h4>Nov 21, 2022</h4>
</center> <!-- date -->
<br>
doc/pub/week47/html/week47-reveal.html
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@@ -184,7 +184,7 @@ MathJax.Hub.Config({
</center>
<br>
<center>
<h4>Nov 20, 2022</h4>
<h4>Nov 21, 2022</h4>
</center> <!-- date -->
<br>
@@ -198,15 +198,21 @@ MathJax.Hub.Config({
<h2 id="overview-of-week-47">Overview of week 47 </h2>
<ul>
<p><li> <b>Thursday</b>: Support Vector Machines, classification and regression.</li>
<p><li> <b>Friday</b>: Support Vector Machines and Summary of Course</li>
<p><li> <b>Thursday</b>: Dimensionality reduction and unsupervised learning: Principal Component analysis (PCA) and clustering</li>
<p><li> <b>Friday</b>: PCA and clustering and Summary of Course</li>
</ul>
<p>
<b>Excellent video</b>:
<ol>
<p><li> We recommend highly the video on PCA by <a href="http://www.databookuw.com/page-2/page-4/" target="_blank">Brunton and Kutz</a>, see in particular the video of section 1.5. Repeating about the singular value discussion is also very useful as we will use this material as background.</li>
<p><li> <a href="https://www.youtube.com/watch?v=FgakZw6K1QQ" target="_blank">And another good video on PCA</a></li>
<p><li> <a href="https://www.youtube.com/watch?v=4b5d3muPQmA" target="_blank">k-means clustering video</a></li>
</ol>
<p>
<p>_Reading recommendations:</p>
<ol>
<p><li> Geron's chapter 5.</li>
<p><li> Hastie et al Chapter 12 (sections 12.1-12.3 are the most relevant ones)</li>
<p><li> Bishop chapter 7, with sections 7.1 and 7.2 as the essential ones</li>
<p><li> Geron's chapter 9 on PCA</li>
<p><li> Hastie et al Chapter 13 (sections 13.1-13.2 are the most relevant ones)</li>
</ol>
</section>
doc/pub/week47/html/week47-solarized.html
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@@ -333,7 +333,7 @@ MathJax.Hub.Config({
</center>
<br>
<center>
<h4>Nov 20, 2022</h4>
<h4>Nov 21, 2022</h4>
</center> <!-- date -->
<br>
@@ -341,14 +341,19 @@ MathJax.Hub.Config({
<h2 id="overview-of-week-47">Overview of week 47 </h2>
<ul>
<li> <b>Thursday</b>: Support Vector Machines, classification and regression.</li>
<li> <b>Friday</b>: Support Vector Machines and Summary of Course</li>
<li> <b>Thursday</b>: Dimensionality reduction and unsupervised learning: Principal Component analysis (PCA) and clustering</li>
<li> <b>Friday</b>: PCA and clustering and Summary of Course</li>
</ul>
<b>Excellent video</b>:
<ol>
<li> We recommend highly the video on PCA by <a href="http://www.databookuw.com/page-2/page-4/" target="_blank">Brunton and Kutz</a>, see in particular the video of section 1.5. Repeating about the singular value discussion is also very useful as we will use this material as background.</li>
<li> <a href="https://www.youtube.com/watch?v=FgakZw6K1QQ" target="_blank">And another good video on PCA</a></li>
<li> <a href="https://www.youtube.com/watch?v=4b5d3muPQmA" target="_blank">k-means clustering video</a></li>
</ol>
<p>_Reading recommendations:</p>
<ol>
<li> Geron's chapter 5.</li>
<li> Hastie et al Chapter 12 (sections 12.1-12.3 are the most relevant ones)</li>
<li> Bishop chapter 7, with sections 7.1 and 7.2 as the essential ones</li>
<li> Geron's chapter 9 on PCA</li>
<li> Hastie et al Chapter 13 (sections 13.1-13.2 are the most relevant ones)</li>
</ol>
<!-- !split --><br><br><br><br><br><br><br><br><br><br>
<h2 id="basic-ideas-of-the-principal-component-analysis-pca">Basic ideas of the Principal Component Analysis (PCA) </h2>
doc/pub/week47/html/week47.html
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@@ -410,7 +410,7 @@ MathJax.Hub.Config({
</center>
<br>
<center>
<h4>Nov 20, 2022</h4>
<h4>Nov 21, 2022</h4>
</center> <!-- date -->
<br>
@@ -418,14 +418,19 @@ MathJax.Hub.Config({
<h2 id="overview-of-week-47">Overview of week 47 </h2>
<ul>
<li> <b>Thursday</b>: Support Vector Machines, classification and regression.</li>
<li> <b>Friday</b>: Support Vector Machines and Summary of Course</li>
<li> <b>Thursday</b>: Dimensionality reduction and unsupervised learning: Principal Component analysis (PCA) and clustering</li>
<li> <b>Friday</b>: PCA and clustering and Summary of Course</li>
</ul>
<b>Excellent video</b>:
<ol>
<li> We recommend highly the video on PCA by <a href="http://www.databookuw.com/page-2/page-4/" target="_blank">Brunton and Kutz</a>, see in particular the video of section 1.5. Repeating about the singular value discussion is also very useful as we will use this material as background.</li>
<li> <a href="https://www.youtube.com/watch?v=FgakZw6K1QQ" target="_blank">And another good video on PCA</a></li>
<li> <a href="https://www.youtube.com/watch?v=4b5d3muPQmA" target="_blank">k-means clustering video</a></li>
</ol>
<p>_Reading recommendations:</p>
<ol>
<li> Geron's chapter 5.</li>
<li> Hastie et al Chapter 12 (sections 12.1-12.3 are the most relevant ones)</li>
<li> Bishop chapter 7, with sections 7.1 and 7.2 as the essential ones</li>
<li> Geron's chapter 9 on PCA</li>
<li> Hastie et al Chapter 13 (sections 13.1-13.2 are the most relevant ones)</li>
</ol>
<!-- !split --><br><br><br><br><br><br><br><br><br><br>
<h2 id="basic-ideas-of-the-principal-component-analysis-pca">Basic ideas of the Principal Component Analysis (PCA) </h2>
doc/pub/week47/ipynb/ipynb-week47-src.tar.gz
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doc/src/week47/week47.do.txt
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@@ -5,14 +5,17 @@ DATE: today
!split
===== Overview of week 47 =====
* _Thursday_: Support Vector Machines, classification and regression.
* _Friday_: Support Vector Machines and Summary of Course
* _Thursday_: Dimensionality reduction and unsupervised learning: Principal Component analysis (PCA) and clustering
* _Friday_: PCA and clustering and Summary of Course
_Excellent video_:
o We recommend highly the video on PCA by "Brunton and Kutz":"http://www.databookuw.com/page-2/page-4/", see in particular the video of section 1.5. Repeating about the singular value discussion is also very useful as we will use this material as background.
o "And another good video on PCA":"https://www.youtube.com/watch?v=FgakZw6K1QQ"
o "k-means clustering video":"https://www.youtube.com/watch?v=4b5d3muPQmA"
_Reading recommendations:
o Geron's chapter 5.
o Hastie et al Chapter 12 (sections 12.1-12.3 are the most relevant ones)
o Bishop chapter 7, with sections 7.1 and 7.2 as the essential ones
o Geron's chapter 9 on PCA
o Hastie et al Chapter 13 (sections 13.1-13.2 are the most relevant ones)