added video on bias-variance

Author: mhjensen

doc/pub/week38/html/._week38-bs001.html

@@ -261,6 +261,7 @@ <h2 id="plans-for-week-38-lecture-monday-september-15" class="anchor">Plans for
 <li> Resampling techniques, Bootstrap and cross validation and bias-variance tradeoff</li>
 <li> The material we did not cover last week, that is on more advanced methods for updating the learning rate, are covered by its own video. We will briefly discuss these topics at the beginning of the lecture and during the lab sessions. See video on ADAgrad, RMSprop and ADAM (material from last week not covered during lecture) at <a href="https://youtu.be/J_41Hld6tTU" target="_self"><tt>https://youtu.be/J_41Hld6tTU</tt></a></li>
 <li> <a href="https://youtu.be/4Fo7ITVA7V4" target="_self">Video of Lecture</a></li>
+<li> <a href="https://youtu.be/GBWc1abChKo" target="_self">Video from lab sessions on the bias-variance tradeoff</a></li>
 <li> <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2025/FYSSTKweek38.pdf" target="_self">Whiteboard notes</a></li>
 </ol>
 </div>

doc/pub/week38/html/week38-reveal.html

@@ -202,6 +202,7 @@ <h2 id="plans-for-week-38-lecture-monday-september-15">Plans for week 38, lectur
 <p><li> Resampling techniques, Bootstrap and cross validation and bias-variance tradeoff</li>
 <p><li> The material we did not cover last week, that is on more advanced methods for updating the learning rate, are covered by its own video. We will briefly discuss these topics at the beginning of the lecture and during the lab sessions. See video on ADAgrad, RMSprop and ADAM (material from last week not covered during lecture) at <a href="https://youtu.be/J_41Hld6tTU" target="_blank"><tt>https://youtu.be/J_41Hld6tTU</tt></a></li>
 <p><li> <a href="https://youtu.be/4Fo7ITVA7V4" target="_blank">Video of Lecture</a></li>
+<p><li> <a href="https://youtu.be/GBWc1abChKo" target="_blank">Video from lab sessions on the bias-variance tradeoff</a></li>
 <p><li> <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2025/FYSSTKweek38.pdf" target="_blank">Whiteboard notes</a></li>
 </ol>
 </div>

doc/pub/week38/html/week38-solarized.html

@@ -240,6 +240,7 @@ <h2 id="plans-for-week-38-lecture-monday-september-15">Plans for week 38, lectur
 <li> Resampling techniques, Bootstrap and cross validation and bias-variance tradeoff</li>
 <li> The material we did not cover last week, that is on more advanced methods for updating the learning rate, are covered by its own video. We will briefly discuss these topics at the beginning of the lecture and during the lab sessions. See video on ADAgrad, RMSprop and ADAM (material from last week not covered during lecture) at <a href="https://youtu.be/J_41Hld6tTU" target="_blank"><tt>https://youtu.be/J_41Hld6tTU</tt></a></li>
 <li> <a href="https://youtu.be/4Fo7ITVA7V4" target="_blank">Video of Lecture</a></li>
+<li> <a href="https://youtu.be/GBWc1abChKo" target="_blank">Video from lab sessions on the bias-variance tradeoff</a></li>
 <li> <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2025/FYSSTKweek38.pdf" target="_blank">Whiteboard notes</a></li>
 </ol>
 </div>

doc/pub/week38/html/week38.html

@@ -317,6 +317,7 @@ <h2 id="plans-for-week-38-lecture-monday-september-15">Plans for week 38, lectur
 <li> Resampling techniques, Bootstrap and cross validation and bias-variance tradeoff</li>
 <li> The material we did not cover last week, that is on more advanced methods for updating the learning rate, are covered by its own video. We will briefly discuss these topics at the beginning of the lecture and during the lab sessions. See video on ADAgrad, RMSprop and ADAM (material from last week not covered during lecture) at <a href="https://youtu.be/J_41Hld6tTU" target="_blank"><tt>https://youtu.be/J_41Hld6tTU</tt></a></li>
 <li> <a href="https://youtu.be/4Fo7ITVA7V4" target="_blank">Video of Lecture</a></li>
+<li> <a href="https://youtu.be/GBWc1abChKo" target="_blank">Video from lab sessions on the bias-variance tradeoff</a></li>
 <li> <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2025/FYSSTKweek38.pdf" target="_blank">Whiteboard notes</a></li>
 </ol>
 </div>