added video

Author: mhjensen

doc/HandWrittenNotes/2025/FYSSTKweek36.pdf

@@ -341,9 +341,9 @@ <h2 id="plans-for-week-36" class="anchor">Plans for week 36 </h2>
 <b>Material for the lecture on Monday September 1:</b>
 <ol>
 <li> Linear Regression, ordinary least squares (OLS), Ridge and Lasso and mathematical analysis</li>
-<li> Derivation of Gradient descent and discussion of implementations for
-<!-- * <a href="https://youtu.be/%3Cspan%20class="x x-first x-last">oHjqjUB36KE" target="_self">Video of lecture</a> -->
-<!-- * <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/%3Cspan%20class="x x-first x-last">2024/NotesSeptember2.pdf" target="_self">Whiteboard notes</a> --></li>
+<li> Derivation of Gradient descent and discussion of implementations for</li>
+<li> Video of lecture at <a href="https://youtu.be/nVE_FRnGAHw" target="_self"><tt>https://youtu.be/nVE_FRnGAHw</tt></a></li>  
+<li> Whiteboard notes at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2025/FYSSTKweek36.pdf" target="_self"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2025/FYSSTKweek36.pdf</tt></a></li>
 </ol>
 <b>Material for the lab sessions on Tuesday and Wednesday (see at the end of these slides):</b>
 <ol>

doc/pub/week36/html/._week36-bs001.html

@@ -197,9 +197,10 @@ <h2 id="plans-for-week-36">Plans for week 36 </h2>
 <b>Material for the lecture on Monday September 1:</b>
 <ol>
 <p><li> Linear Regression, ordinary least squares (OLS), Ridge and Lasso and mathematical analysis</li>
-<p><li> Derivation of Gradient descent and discussion of implementations for
-<!-- * <a href="https://youtu.be/oHjqjUB36KE" target="_blank">Video of lecture</a> -->
-<!-- * <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2024/NotesSeptember2.pdf" target="_blank">Whiteboard notes</a> --></li>
+<p><li> Derivation of Gradient descent and discussion of implementations for</li>
+<p><li> Video of lecture at <a href="https://youtu.be/nVE_FRnGAHw" target="_blank"><tt>https://youtu.be/nVE_FRnGAHw</tt></a></li>
+
+<p><li> Whiteboard notes at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2025/FYSSTKweek36.pdf" target="_blank"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2025/FYSSTKweek36.pdf</tt></a></li>
 </ol>
 <p>
 <b>Material for the lab sessions on Tuesday and Wednesday (see at the end of these slides):</b>

doc/pub/week36/html/week36-reveal.html

@@ -291,9 +291,9 @@ <h2 id="plans-for-week-36">Plans for week 36 </h2>
 <b>Material for the lecture on Monday September 1:</b>
 <ol>
 <li> Linear Regression, ordinary least squares (OLS), Ridge and Lasso and mathematical analysis</li>
-<li> Derivation of Gradient descent and discussion of implementations for
-<!-- * <a href="https://youtu.be/%3Cspan%20class="x x-first x-last">oHjqjUB36KE" target="_blank">Video of lecture</a> -->
-<!-- * <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/%3Cspan%20class="x x-first x-last">2024/NotesSeptember2.pdf" target="_blank">Whiteboard notes</a> --></li>
+<li> Derivation of Gradient descent and discussion of implementations for</li>
+<li> Video of lecture at <a href="https://youtu.be/nVE_FRnGAHw" target="_blank"><tt>https://youtu.be/nVE_FRnGAHw</tt></a></li>  
+<li> Whiteboard notes at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2025/FYSSTKweek36.pdf" target="_blank"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2025/FYSSTKweek36.pdf</tt></a></li>
 </ol>
 <b>Material for the lab sessions on Tuesday and Wednesday (see at the end of these slides):</b>
 <ol>

doc/pub/week36/html/week36-solarized.html

@@ -368,9 +368,9 @@ <h2 id="plans-for-week-36">Plans for week 36 </h2>
 <b>Material for the lecture on Monday September 1:</b>
 <ol>
 <li> Linear Regression, ordinary least squares (OLS), Ridge and Lasso and mathematical analysis</li>
-<li> Derivation of Gradient descent and discussion of implementations for
-<!-- * <a href="https://youtu.be/%3Cspan%20class="x x-first x-last">oHjqjUB36KE" target="_blank">Video of lecture</a> -->
-<!-- * <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/%3Cspan%20class="x x-first x-last">2024/NotesSeptember2.pdf" target="_blank">Whiteboard notes</a> --></li>
+<li> Derivation of Gradient descent and discussion of implementations for</li>
+<li> Video of lecture at <a href="https://youtu.be/nVE_FRnGAHw" target="_blank"><tt>https://youtu.be/nVE_FRnGAHw</tt></a></li>  
+<li> Whiteboard notes at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2025/FYSSTKweek36.pdf" target="_blank"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2025/FYSSTKweek36.pdf</tt></a></li>
 </ol>
 <b>Material for the lab sessions on Tuesday and Wednesday (see at the end of these slides):</b>
 <ol>