diff --git a/doc/pub/week41/html/week41-bs.html b/doc/pub/week41/html/week41-bs.html
index 608f3ab70..3dddc7eed 100644
--- a/doc/pub/week41/html/week41-bs.html
+++ b/doc/pub/week41/html/week41-bs.html
@@ -44,6 +44,7 @@ doconce format html week41.do.txt --html_style=bootstrap --pygments_html_style=d
                2,
                None,
                'material-for-the-lecture-on-monday-october-6-2025'),
+              ('Readings and Videos:', 2, None, 'readings-and-videos'),
               ('Mathematics of deep learning',
                2,
                None,
@@ -330,6 +331,7 @@ MathJax.Hub.Config({
         <ul class="dropdown-menu">
      <!-- navigation toc: --> <li><a href="#plan-for-week-41-october-6-10" style="font-size: 80%;">Plan for week 41, October 6-10</a></li>
      <!-- navigation toc: --> <li><a href="#material-for-the-lecture-on-monday-october-6-2025" style="font-size: 80%;">Material for the lecture on Monday October 6, 2025</a></li>
+     <!-- navigation toc: --> <li><a href="#readings-and-videos" style="font-size: 80%;">Readings and Videos:</a></li>
      <!-- navigation toc: --> <li><a href="#mathematics-of-deep-learning" style="font-size: 80%;">Mathematics of deep learning</a></li>
      <!-- navigation toc: --> <li><a href="#reminder-on-books-with-hands-on-material-and-codes" style="font-size: 80%;">Reminder on books with hands-on material and codes</a></li>
      <!-- navigation toc: --> <li><a href="#lab-sessions-on-tuesday-and-wednesday" style="font-size: 80%;">Lab sessions on Tuesday and Wednesday</a></li>
@@ -452,24 +454,24 @@ MathJax.Hub.Config({
 <ol>
 <li> Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model.</li>
 <li> Building our own Feed-forward Neural Network, getting started
-<!-- * Video of lecture notes at <a href="https://youtu.be/pMRUbf9E-gM" target="_self"><tt>https://youtu.be/pMRUbf9E-gM</tt></a> -->
-<!-- * Whiteboard notes at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2024/NotesOctober7.pdf" target="_self"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2024/NotesOctober7.pdf</tt></a> --></li>
+<!-- * Video of lecture notes at URL:"" -->
+<!-- * Whiteboard notes at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2025/FYSSTKweek41.pdf" target="_self"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2025/FYSSTKweek41.pdf</tt></a> --></li>
 </ol>
+<!-- !split -->
+<h2 id="readings-and-videos" class="anchor">Readings and Videos: </h2>
 <div class="panel panel-default">
 <div class="panel-body">
 <!-- subsequent paragraphs come in larger fonts, so start with a paragraph -->
 <ol>
 <li> These lecture notes</li>
 <li> For neural networks we recommend Goodfellow et al chapters 6 and 7.</li>
-<li> Rashkca et al., chapter 11, jupyter-notebook sent separately, from <a href="https://github.com/rasbt/machine-learning-book" target="_self">GitHub</a>
-<ol type="a"></li>
+<li> Rashkca et al., chapter 11, jupyter-notebook sent separately, from <a href="https://github.com/rasbt/machine-learning-book" target="_self">GitHub</a></li>
 <li> Neural Networks demystified at <a href="https://www.youtube.com/watch?v=bxe2T-V8XRs&list=PLiaHhY2iBX9hdHaRr6b7XevZtgZRa1PoU&ab_channel=WelchLabs" target="_self"><tt>https://www.youtube.com/watch?v=bxe2T-V8XRs&list=PLiaHhY2iBX9hdHaRr6b7XevZtgZRa1PoU&ab_channel=WelchLabs</tt></a></li>
-</ol>
 <li> Building Neural Networks from scratch at <a href="https://www.youtube.com/watch?v=Wo5dMEP_BbI&list=PLQVvvaa0QuDcjD5BAw2DxE6OF2tius3V3&ab_channel=sentdex" target="_self"><tt>https://www.youtube.com/watch?v=Wo5dMEP_BbI&list=PLQVvvaa0QuDcjD5BAw2DxE6OF2tius3V3&ab_channel=sentdex</tt></a></li>
 <li> Video on Neural Networks at <a href="https://www.youtube.com/watch?v=CqOfi41LfDw" target="_self"><tt>https://www.youtube.com/watch?v=CqOfi41LfDw</tt></a></li>
 <li> Video on the back propagation algorithm at <a href="https://www.youtube.com/watch?v=Ilg3gGewQ5U" target="_self"><tt>https://www.youtube.com/watch?v=Ilg3gGewQ5U</tt></a></li>
+<li> We also  recommend Michael Nielsen's intuitive approach to the neural networks and the universal approximation theorem, see the slides at <a href="http://neuralnetworksanddeeplearning.com/chap4.html" target="_self"><tt>http://neuralnetworksanddeeplearning.com/chap4.html</tt></a>.</li>
 </ol>
-<p>We also  recommend Michael Nielsen's intuitive approach to the neural networks and the universal approximation theorem, see the slides at <a href="http://neuralnetworksanddeeplearning.com/chap4.html" target="_self"><tt>http://neuralnetworksanddeeplearning.com/chap4.html</tt></a>.</p>
 </div>
 </div>
 
@@ -493,9 +495,7 @@ MathJax.Hub.Config({
 <div class="panel panel-default">
 <div class="panel-body">
 <!-- subsequent paragraphs come in larger fonts, so start with a paragraph -->
-<ul>
-<li> <a href="https://sebastianraschka.com/blog/2022/ml-pytorch-book.html" target="_self">Sebastian Rashcka et al, Machine learning with Sickit-Learn and PyTorch</a></li>
-</ul>
+<a href="https://sebastianraschka.com/blog/2022/ml-pytorch-book.html" target="_self">Sebastian Rashcka et al, Machine learning with Sickit-Learn and PyTorch</a>
 </div>
 </div>
 
@@ -503,9 +503,10 @@ MathJax.Hub.Config({
 <!-- !split -->
 <h2 id="lab-sessions-on-tuesday-and-wednesday" class="anchor">Lab sessions on Tuesday and Wednesday </h2>
 
-<ol>
-<li> Getting started with coding neural network. The exercises this week aim at setting up the feed-forward part of a neural network.</li>
-</ol>
+<p>Aim: Getting started with coding neural network. The exercises this
+week aim at setting up the feed-forward part of a neural network.
+</p>
+
 <!-- !split -->
 <h2 id="lecture-monday-october-6" class="anchor">Lecture Monday  October 6 </h2>
 
diff --git a/doc/pub/week41/html/week41-reveal.html b/doc/pub/week41/html/week41-reveal.html
index f973c8ef4..bab4fc34e 100644
--- a/doc/pub/week41/html/week41-reveal.html
+++ b/doc/pub/week41/html/week41-reveal.html
@@ -200,27 +200,26 @@ MathJax.Hub.Config({
 <ol>
 <p><li> Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model.</li>
 <p><li> Building our own Feed-forward Neural Network, getting started
-<!-- * Video of lecture notes at <a href="https://youtu.be/pMRUbf9E-gM" target="_blank"><tt>https://youtu.be/pMRUbf9E-gM</tt></a> -->
-<!-- * Whiteboard notes at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2024/NotesOctober7.pdf" target="_blank"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2024/NotesOctober7.pdf</tt></a> --></li>
+<!-- * Video of lecture notes at URL:"" -->
+<!-- * Whiteboard notes at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2025/FYSSTKweek41.pdf" target="_blank"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2025/FYSSTKweek41.pdf</tt></a> --></li>
 </ol>
-<p>
+</section>
+
+<section>
+<h2 id="readings-and-videos">Readings and Videos: </h2>
 <div class="alert alert-block alert-block alert-text-normal">
-<b>Readings and Videos:</b>
+<b></b>
 <p>
 <ol>
 <p><li> These lecture notes</li>
 <p><li> For neural networks we recommend Goodfellow et al chapters 6 and 7.</li>
-<p><li> Rashkca et al., chapter 11, jupyter-notebook sent separately, from <a href="https://github.com/rasbt/machine-learning-book" target="_blank">GitHub</a>
-<ol type="a"></li>
+<p><li> Rashkca et al., chapter 11, jupyter-notebook sent separately, from <a href="https://github.com/rasbt/machine-learning-book" target="_blank">GitHub</a></li>
 <p><li> Neural Networks demystified at <a href="https://www.youtube.com/watch?v=bxe2T-V8XRs&list=PLiaHhY2iBX9hdHaRr6b7XevZtgZRa1PoU&ab_channel=WelchLabs" target="_blank"><tt>https://www.youtube.com/watch?v=bxe2T-V8XRs&list=PLiaHhY2iBX9hdHaRr6b7XevZtgZRa1PoU&ab_channel=WelchLabs</tt></a></li>
-</ol>
-<p>
 <p><li> Building Neural Networks from scratch at <a href="https://www.youtube.com/watch?v=Wo5dMEP_BbI&list=PLQVvvaa0QuDcjD5BAw2DxE6OF2tius3V3&ab_channel=sentdex" target="_blank"><tt>https://www.youtube.com/watch?v=Wo5dMEP_BbI&list=PLQVvvaa0QuDcjD5BAw2DxE6OF2tius3V3&ab_channel=sentdex</tt></a></li>
 <p><li> Video on Neural Networks at <a href="https://www.youtube.com/watch?v=CqOfi41LfDw" target="_blank"><tt>https://www.youtube.com/watch?v=CqOfi41LfDw</tt></a></li>
 <p><li> Video on the back propagation algorithm at <a href="https://www.youtube.com/watch?v=Ilg3gGewQ5U" target="_blank"><tt>https://www.youtube.com/watch?v=Ilg3gGewQ5U</tt></a></li>
+<p><li> We also  recommend Michael Nielsen's intuitive approach to the neural networks and the universal approximation theorem, see the slides at <a href="http://neuralnetworksanddeeplearning.com/chap4.html" target="_blank"><tt>http://neuralnetworksanddeeplearning.com/chap4.html</tt></a>.</li>
 </ol>
-<p>
-<p>We also  recommend Michael Nielsen's intuitive approach to the neural networks and the universal approximation theorem, see the slides at <a href="http://neuralnetworksanddeeplearning.com/chap4.html" target="_blank"><tt>http://neuralnetworksanddeeplearning.com/chap4.html</tt></a>.</p>
 </div>
 </section>
 
@@ -242,18 +241,16 @@ MathJax.Hub.Config({
 <div class="alert alert-block alert-block alert-text-normal">
 <b></b>
 <p>
-<ul>
-<p><li> <a href="https://sebastianraschka.com/blog/2022/ml-pytorch-book.html" target="_blank">Sebastian Rashcka et al, Machine learning with Sickit-Learn and PyTorch</a></li>
-</ul>
+<a href="https://sebastianraschka.com/blog/2022/ml-pytorch-book.html" target="_blank">Sebastian Rashcka et al, Machine learning with Sickit-Learn and PyTorch</a>
 </div>
 </section>
 
 <section>
 <h2 id="lab-sessions-on-tuesday-and-wednesday">Lab sessions on Tuesday and Wednesday </h2>
 
-<ol>
-<p><li> Getting started with coding neural network. The exercises this week aim at setting up the feed-forward part of a neural network.</li>
-</ol>
+<p>Aim: Getting started with coding neural network. The exercises this
+week aim at setting up the feed-forward part of a neural network.
+</p>
 </section>
 
 <section>
diff --git a/doc/pub/week41/html/week41-solarized.html b/doc/pub/week41/html/week41-solarized.html
index 7e5ee66e3..205604842 100644
--- a/doc/pub/week41/html/week41-solarized.html
+++ b/doc/pub/week41/html/week41-solarized.html
@@ -71,6 +71,7 @@ div.toc p,a {
                2,
                None,
                'material-for-the-lecture-on-monday-october-6-2025'),
+              ('Readings and Videos:', 2, None, 'readings-and-videos'),
               ('Mathematics of deep learning',
                2,
                None,
@@ -367,24 +368,24 @@ MathJax.Hub.Config({
 <ol>
 <li> Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model.</li>
 <li> Building our own Feed-forward Neural Network, getting started
-<!-- * Video of lecture notes at <a href="https://youtu.be/pMRUbf9E-gM" target="_blank"><tt>https://youtu.be/pMRUbf9E-gM</tt></a> -->
-<!-- * Whiteboard notes at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2024/NotesOctober7.pdf" target="_blank"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2024/NotesOctober7.pdf</tt></a> --></li>
+<!-- * Video of lecture notes at URL:"" -->
+<!-- * Whiteboard notes at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2025/FYSSTKweek41.pdf" target="_blank"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2025/FYSSTKweek41.pdf</tt></a> --></li>
 </ol>
+<!-- !split --><br><br><br><br><br><br><br><br><br><br>
+<h2 id="readings-and-videos">Readings and Videos: </h2>
 <div class="alert alert-block alert-block alert-text-normal">
-<b>Readings and Videos:</b>
+<b></b>
 <p>
 <ol>
 <li> These lecture notes</li>
 <li> For neural networks we recommend Goodfellow et al chapters 6 and 7.</li>
-<li> Rashkca et al., chapter 11, jupyter-notebook sent separately, from <a href="https://github.com/rasbt/machine-learning-book" target="_blank">GitHub</a>
-<ol type="a"></li>
+<li> Rashkca et al., chapter 11, jupyter-notebook sent separately, from <a href="https://github.com/rasbt/machine-learning-book" target="_blank">GitHub</a></li>
 <li> Neural Networks demystified at <a href="https://www.youtube.com/watch?v=bxe2T-V8XRs&list=PLiaHhY2iBX9hdHaRr6b7XevZtgZRa1PoU&ab_channel=WelchLabs" target="_blank"><tt>https://www.youtube.com/watch?v=bxe2T-V8XRs&list=PLiaHhY2iBX9hdHaRr6b7XevZtgZRa1PoU&ab_channel=WelchLabs</tt></a></li>
-</ol>
 <li> Building Neural Networks from scratch at <a href="https://www.youtube.com/watch?v=Wo5dMEP_BbI&list=PLQVvvaa0QuDcjD5BAw2DxE6OF2tius3V3&ab_channel=sentdex" target="_blank"><tt>https://www.youtube.com/watch?v=Wo5dMEP_BbI&list=PLQVvvaa0QuDcjD5BAw2DxE6OF2tius3V3&ab_channel=sentdex</tt></a></li>
 <li> Video on Neural Networks at <a href="https://www.youtube.com/watch?v=CqOfi41LfDw" target="_blank"><tt>https://www.youtube.com/watch?v=CqOfi41LfDw</tt></a></li>
 <li> Video on the back propagation algorithm at <a href="https://www.youtube.com/watch?v=Ilg3gGewQ5U" target="_blank"><tt>https://www.youtube.com/watch?v=Ilg3gGewQ5U</tt></a></li>
+<li> We also  recommend Michael Nielsen's intuitive approach to the neural networks and the universal approximation theorem, see the slides at <a href="http://neuralnetworksanddeeplearning.com/chap4.html" target="_blank"><tt>http://neuralnetworksanddeeplearning.com/chap4.html</tt></a>.</li>
 </ol>
-<p>We also  recommend Michael Nielsen's intuitive approach to the neural networks and the universal approximation theorem, see the slides at <a href="http://neuralnetworksanddeeplearning.com/chap4.html" target="_blank"><tt>http://neuralnetworksanddeeplearning.com/chap4.html</tt></a>.</p>
 </div>
 
 
@@ -406,18 +407,17 @@ MathJax.Hub.Config({
 <div class="alert alert-block alert-block alert-text-normal">
 <b></b>
 <p>
-<ul>
-<li> <a href="https://sebastianraschka.com/blog/2022/ml-pytorch-book.html" target="_blank">Sebastian Rashcka et al, Machine learning with Sickit-Learn and PyTorch</a></li>
-</ul>
+<a href="https://sebastianraschka.com/blog/2022/ml-pytorch-book.html" target="_blank">Sebastian Rashcka et al, Machine learning with Sickit-Learn and PyTorch</a>
 </div>
 
 
 <!-- !split --><br><br><br><br><br><br><br><br><br><br>
 <h2 id="lab-sessions-on-tuesday-and-wednesday">Lab sessions on Tuesday and Wednesday </h2>
 
-<ol>
-<li> Getting started with coding neural network. The exercises this week aim at setting up the feed-forward part of a neural network.</li>
-</ol>
+<p>Aim: Getting started with coding neural network. The exercises this
+week aim at setting up the feed-forward part of a neural network.
+</p>
+
 <!-- !split --><br><br><br><br><br><br><br><br><br><br>
 <h2 id="lecture-monday-october-6">Lecture Monday  October 6 </h2>
 
diff --git a/doc/pub/week41/html/week41.html b/doc/pub/week41/html/week41.html
index 91136689d..8a6d24872 100644
--- a/doc/pub/week41/html/week41.html
+++ b/doc/pub/week41/html/week41.html
@@ -148,6 +148,7 @@ div.toc p,a {
                2,
                None,
                'material-for-the-lecture-on-monday-october-6-2025'),
+              ('Readings and Videos:', 2, None, 'readings-and-videos'),
               ('Mathematics of deep learning',
                2,
                None,
@@ -444,24 +445,24 @@ MathJax.Hub.Config({
 <ol>
 <li> Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model.</li>
 <li> Building our own Feed-forward Neural Network, getting started
-<!-- * Video of lecture notes at <a href="https://youtu.be/pMRUbf9E-gM" target="_blank"><tt>https://youtu.be/pMRUbf9E-gM</tt></a> -->
-<!-- * Whiteboard notes at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2024/NotesOctober7.pdf" target="_blank"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2024/NotesOctober7.pdf</tt></a> --></li>
+<!-- * Video of lecture notes at URL:"" -->
+<!-- * Whiteboard notes at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2025/FYSSTKweek41.pdf" target="_blank"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2025/FYSSTKweek41.pdf</tt></a> --></li>
 </ol>
+<!-- !split --><br><br><br><br><br><br><br><br><br><br>
+<h2 id="readings-and-videos">Readings and Videos: </h2>
 <div class="alert alert-block alert-block alert-text-normal">
-<b>Readings and Videos:</b>
+<b></b>
 <p>
 <ol>
 <li> These lecture notes</li>
 <li> For neural networks we recommend Goodfellow et al chapters 6 and 7.</li>
-<li> Rashkca et al., chapter 11, jupyter-notebook sent separately, from <a href="https://github.com/rasbt/machine-learning-book" target="_blank">GitHub</a>
-<ol type="a"></li>
+<li> Rashkca et al., chapter 11, jupyter-notebook sent separately, from <a href="https://github.com/rasbt/machine-learning-book" target="_blank">GitHub</a></li>
 <li> Neural Networks demystified at <a href="https://www.youtube.com/watch?v=bxe2T-V8XRs&list=PLiaHhY2iBX9hdHaRr6b7XevZtgZRa1PoU&ab_channel=WelchLabs" target="_blank"><tt>https://www.youtube.com/watch?v=bxe2T-V8XRs&list=PLiaHhY2iBX9hdHaRr6b7XevZtgZRa1PoU&ab_channel=WelchLabs</tt></a></li>
-</ol>
 <li> Building Neural Networks from scratch at <a href="https://www.youtube.com/watch?v=Wo5dMEP_BbI&list=PLQVvvaa0QuDcjD5BAw2DxE6OF2tius3V3&ab_channel=sentdex" target="_blank"><tt>https://www.youtube.com/watch?v=Wo5dMEP_BbI&list=PLQVvvaa0QuDcjD5BAw2DxE6OF2tius3V3&ab_channel=sentdex</tt></a></li>
 <li> Video on Neural Networks at <a href="https://www.youtube.com/watch?v=CqOfi41LfDw" target="_blank"><tt>https://www.youtube.com/watch?v=CqOfi41LfDw</tt></a></li>
 <li> Video on the back propagation algorithm at <a href="https://www.youtube.com/watch?v=Ilg3gGewQ5U" target="_blank"><tt>https://www.youtube.com/watch?v=Ilg3gGewQ5U</tt></a></li>
+<li> We also  recommend Michael Nielsen's intuitive approach to the neural networks and the universal approximation theorem, see the slides at <a href="http://neuralnetworksanddeeplearning.com/chap4.html" target="_blank"><tt>http://neuralnetworksanddeeplearning.com/chap4.html</tt></a>.</li>
 </ol>
-<p>We also  recommend Michael Nielsen's intuitive approach to the neural networks and the universal approximation theorem, see the slides at <a href="http://neuralnetworksanddeeplearning.com/chap4.html" target="_blank"><tt>http://neuralnetworksanddeeplearning.com/chap4.html</tt></a>.</p>
 </div>
 
 
@@ -483,18 +484,17 @@ MathJax.Hub.Config({
 <div class="alert alert-block alert-block alert-text-normal">
 <b></b>
 <p>
-<ul>
-<li> <a href="https://sebastianraschka.com/blog/2022/ml-pytorch-book.html" target="_blank">Sebastian Rashcka et al, Machine learning with Sickit-Learn and PyTorch</a></li>
-</ul>
+<a href="https://sebastianraschka.com/blog/2022/ml-pytorch-book.html" target="_blank">Sebastian Rashcka et al, Machine learning with Sickit-Learn and PyTorch</a>
 </div>
 
 
 <!-- !split --><br><br><br><br><br><br><br><br><br><br>
 <h2 id="lab-sessions-on-tuesday-and-wednesday">Lab sessions on Tuesday and Wednesday </h2>
 
-<ol>
-<li> Getting started with coding neural network. The exercises this week aim at setting up the feed-forward part of a neural network.</li>
-</ol>
+<p>Aim: Getting started with coding neural network. The exercises this
+week aim at setting up the feed-forward part of a neural network.
+</p>
+
 <!-- !split --><br><br><br><br><br><br><br><br><br><br>
 <h2 id="lecture-monday-october-6">Lecture Monday  October 6 </h2>
 
diff --git a/doc/pub/week41/ipynb/ipynb-week41-src.tar.gz b/doc/pub/week41/ipynb/ipynb-week41-src.tar.gz
index 1e2e85473..f9e5ab5a9 100644
Binary files a/doc/pub/week41/ipynb/ipynb-week41-src.tar.gz and b/doc/pub/week41/ipynb/ipynb-week41-src.tar.gz differ
diff --git a/doc/pub/week41/ipynb/week41.ipynb b/doc/pub/week41/ipynb/week41.ipynb
index a70cfa378..c9b1adcdd 100644
--- a/doc/pub/week41/ipynb/week41.ipynb
+++ b/doc/pub/week41/ipynb/week41.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "009b0d42",
+   "id": "b625bb28",
    "metadata": {
     "editable": true
    },
@@ -14,7 +14,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "77106a5c",
+   "id": "679109d4",
    "metadata": {
     "editable": true
    },
@@ -27,7 +27,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "24abde37",
+   "id": "d7401ab9",
    "metadata": {
     "editable": true
    },
@@ -37,7 +37,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f046f2f8",
+   "id": "f47e1c5c",
    "metadata": {
     "editable": true
    },
@@ -46,31 +46,38 @@
     "1. Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model.\n",
     "\n",
     "2. Building our own Feed-forward Neural Network, getting started\n",
-    "<!-- * Video of lecture notes at <https://youtu.be/pMRUbf9E-gM> -->\n",
-    "<!-- * Whiteboard notes at <https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2024/NotesOctober7.pdf> -->\n",
-    "\n",
-    "**Readings and Videos:**\n",
-    "\n",
+    "<!-- * Video of lecture notes at URL:\"\" -->\n",
+    "<!-- * Whiteboard notes at <https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2025/FYSSTKweek41.pdf> -->"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "af0a9895",
+   "metadata": {
+    "editable": true
+   },
+   "source": [
+    "## Readings and Videos:\n",
     "1. These lecture notes\n",
     "\n",
     "2. For neural networks we recommend Goodfellow et al chapters 6 and 7.\n",
     "\n",
     "3. Rashkca et al., chapter 11, jupyter-notebook sent separately, from [GitHub](https://github.com/rasbt/machine-learning-book)\n",
     "\n",
-    "a. Neural Networks demystified at <https://www.youtube.com/watch?v=bxe2T-V8XRs&list=PLiaHhY2iBX9hdHaRr6b7XevZtgZRa1PoU&ab_channel=WelchLabs>\n",
+    "4. Neural Networks demystified at <https://www.youtube.com/watch?v=bxe2T-V8XRs&list=PLiaHhY2iBX9hdHaRr6b7XevZtgZRa1PoU&ab_channel=WelchLabs>\n",
     "\n",
-    "2. Building Neural Networks from scratch at <https://www.youtube.com/watch?v=Wo5dMEP_BbI&list=PLQVvvaa0QuDcjD5BAw2DxE6OF2tius3V3&ab_channel=sentdex>\n",
+    "5. Building Neural Networks from scratch at <https://www.youtube.com/watch?v=Wo5dMEP_BbI&list=PLQVvvaa0QuDcjD5BAw2DxE6OF2tius3V3&ab_channel=sentdex>\n",
     "\n",
-    "3. Video on Neural Networks at <https://www.youtube.com/watch?v=CqOfi41LfDw>\n",
+    "6. Video on Neural Networks at <https://www.youtube.com/watch?v=CqOfi41LfDw>\n",
     "\n",
-    "4. Video on the back propagation algorithm at <https://www.youtube.com/watch?v=Ilg3gGewQ5U>\n",
+    "7. Video on the back propagation algorithm at <https://www.youtube.com/watch?v=Ilg3gGewQ5U>\n",
     "\n",
-    "We also  recommend Michael Nielsen's intuitive approach to the neural networks and the universal approximation theorem, see the slides at <http://neuralnetworksanddeeplearning.com/chap4.html>."
+    "8. We also  recommend Michael Nielsen's intuitive approach to the neural networks and the universal approximation theorem, see the slides at <http://neuralnetworksanddeeplearning.com/chap4.html>."
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "083a57fa",
+   "id": "be1e5c03",
    "metadata": {
     "editable": true
    },
@@ -86,30 +93,31 @@
   },
   {
    "cell_type": "markdown",
-   "id": "afd44c9c",
+   "id": "52520e8f",
    "metadata": {
     "editable": true
    },
    "source": [
     "## Reminder on books with hands-on material and codes\n",
-    "* [Sebastian Rashcka et al, Machine learning with Sickit-Learn and PyTorch](https://sebastianraschka.com/blog/2022/ml-pytorch-book.html)"
+    "[Sebastian Rashcka et al, Machine learning with Sickit-Learn and PyTorch](https://sebastianraschka.com/blog/2022/ml-pytorch-book.html)"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "a635e90e",
+   "id": "408a0487",
    "metadata": {
     "editable": true
    },
    "source": [
     "## Lab sessions on Tuesday and Wednesday\n",
     "\n",
-    "1. Getting started with coding neural network. The exercises this week aim at setting up the feed-forward part of a neural network."
+    "Aim: Getting started with coding neural network. The exercises this\n",
+    "week aim at setting up the feed-forward part of a neural network."
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "117eee5e",
+   "id": "23056baf",
    "metadata": {
     "editable": true
    },
@@ -119,7 +127,7 @@
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   {
    "cell_type": "markdown",
-   "id": "b17ac07a",
+   "id": "56a2f2f2",
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@@ -137,7 +145,7 @@
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   {
    "cell_type": "markdown",
-   "id": "9fabd88e",
+   "id": "2e3fa93d",
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@@ -161,7 +169,7 @@
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   {
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-   "id": "4e03559d",
+   "id": "0afafe3e",
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@@ -179,7 +187,7 @@
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   {
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-   "id": "797b27ee",
+   "id": "bc113056",
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@@ -219,7 +227,7 @@
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   {
    "cell_type": "markdown",
-   "id": "3ac6b2d0",
+   "id": "872c3321",
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@@ -248,7 +256,7 @@
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   {
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-   "id": "58d8729d",
+   "id": "53edae74",
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@@ -269,7 +277,7 @@
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   {
    "cell_type": "markdown",
-   "id": "7a91bacc",
+   "id": "0eef36d6",
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@@ -298,7 +306,7 @@
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   {
    "cell_type": "markdown",
-   "id": "811d80fc",
+   "id": "bf602451",
    "metadata": {
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@@ -319,7 +327,7 @@
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    "cell_type": "markdown",
-   "id": "755de74a",
+   "id": "0afbe2d0",
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@@ -340,7 +348,7 @@
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   {
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-   "id": "3e5ada1e",
+   "id": "d957cfe8",
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@@ -357,7 +365,7 @@
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   {
    "cell_type": "markdown",
-   "id": "39a52a85",
+   "id": "57b218ab",
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@@ -378,7 +386,7 @@
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-   "id": "b6dfa1a1",
+   "id": "6bda8dda",
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@@ -394,7 +402,7 @@
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+   "id": "f7d514be",
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@@ -413,7 +421,7 @@
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-   "id": "a6350e9a",
+   "id": "02ed299b",
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@@ -437,7 +445,7 @@
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   {
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-   "id": "747e12b0",
+   "id": "96b8c13c",
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@@ -464,7 +472,7 @@
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   {
    "cell_type": "markdown",
-   "id": "854e3306",
+   "id": "089704bf",
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@@ -481,7 +489,7 @@
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-   "id": "be6f6f3a",
+   "id": "91ef7170",
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@@ -493,7 +501,7 @@
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   {
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-   "id": "6b12c77c",
+   "id": "c9402737",
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@@ -504,7 +512,7 @@
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-   "id": "5b36bfaf",
+   "id": "09940e05",
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@@ -522,7 +530,7 @@
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-   "id": "4f6a7c65",
+   "id": "2bd7b3ff",
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@@ -551,7 +559,7 @@
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    "cell_type": "markdown",
-   "id": "fa362d11",
+   "id": "1a771f02",
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@@ -565,7 +573,7 @@
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-   "id": "be99467f",
+   "id": "3291a232",
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@@ -581,7 +589,7 @@
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-   "id": "a7786a41",
+   "id": "74cc209d",
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@@ -593,7 +601,7 @@
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   {
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-   "id": "0ee49876",
+   "id": "fe210f2f",
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@@ -607,7 +615,7 @@
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-   "id": "5907b6b3",
+   "id": "4dfec9c9",
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@@ -619,7 +627,7 @@
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   {
    "cell_type": "markdown",
-   "id": "f5243715",
+   "id": "a65f0cd5",
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@@ -635,7 +643,7 @@
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   {
    "cell_type": "markdown",
-   "id": "3ec7c025",
+   "id": "d006386b",
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@@ -651,7 +659,7 @@
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   {
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-   "id": "00614dd5",
+   "id": "0b094d43",
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@@ -663,7 +671,7 @@
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   {
    "cell_type": "markdown",
-   "id": "3e3c5d32",
+   "id": "f2b9ca56",
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@@ -673,7 +681,7 @@
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   {
    "cell_type": "markdown",
-   "id": "3d292016",
+   "id": "db4817b0",
    "metadata": {
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@@ -685,7 +693,7 @@
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   {
    "cell_type": "markdown",
-   "id": "ffccfb34",
+   "id": "43216143",
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@@ -703,7 +711,7 @@
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   {
    "cell_type": "markdown",
-   "id": "18364a7b",
+   "id": "ef48ad88",
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@@ -716,7 +724,7 @@
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   {
    "cell_type": "markdown",
-   "id": "4ff3f75c",
+   "id": "7c4fed36",
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@@ -733,7 +741,7 @@
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   {
    "cell_type": "markdown",
-   "id": "e2110836",
+   "id": "c4cf04e8",
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@@ -745,7 +753,7 @@
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   {
    "cell_type": "markdown",
-   "id": "86b8cfca",
+   "id": "ecc9a1bd",
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@@ -757,7 +765,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6accc6fd",
+   "id": "91e6e150",
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@@ -773,7 +781,7 @@
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   {
    "cell_type": "markdown",
-   "id": "a7658d1e",
+   "id": "4fabe3cc",
    "metadata": {
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@@ -790,7 +798,7 @@
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   {
    "cell_type": "markdown",
-   "id": "5c32377f",
+   "id": "8c25e4cf",
    "metadata": {
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@@ -802,7 +810,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "fe50869b",
+   "id": "ae861380",
    "metadata": {
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@@ -815,7 +823,7 @@
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   {
    "cell_type": "markdown",
-   "id": "ebaa515a",
+   "id": "2b7f7b74",
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@@ -827,7 +835,7 @@
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   {
    "cell_type": "markdown",
-   "id": "796833f6",
+   "id": "e76386ca",
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@@ -843,7 +851,7 @@
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   {
    "cell_type": "markdown",
-   "id": "ee384d06",
+   "id": "12a9fb38",
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@@ -855,7 +863,7 @@
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   {
    "cell_type": "markdown",
-   "id": "27fdce89",
+   "id": "08bbe824",
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@@ -867,7 +875,7 @@
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   {
    "cell_type": "markdown",
-   "id": "20c880e6",
+   "id": "3783fe53",
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@@ -879,7 +887,7 @@
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   {
    "cell_type": "markdown",
-   "id": "9c0f588a",
+   "id": "2b70d213",
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@@ -889,7 +897,7 @@
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   {
    "cell_type": "markdown",
-   "id": "4967d9dc",
+   "id": "209db1b2",
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@@ -901,7 +909,7 @@
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   {
    "cell_type": "markdown",
-   "id": "e16de9db",
+   "id": "6e42f02f",
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@@ -911,7 +919,7 @@
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   {
    "cell_type": "markdown",
-   "id": "f8640493",
+   "id": "78422fdc",
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@@ -923,7 +931,7 @@
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   {
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-   "id": "9aa93ac0",
+   "id": "8c8491cf",
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@@ -937,7 +945,7 @@
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   {
    "cell_type": "markdown",
-   "id": "14cc2a9c",
+   "id": "82fb3ded",
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@@ -949,7 +957,7 @@
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   {
    "cell_type": "markdown",
-   "id": "0cfa4223",
+   "id": "88fe7049",
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@@ -959,7 +967,7 @@
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   {
    "cell_type": "markdown",
-   "id": "9c28ca56",
+   "id": "af856571",
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@@ -971,7 +979,7 @@
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   {
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-   "id": "75fc65a8",
+   "id": "d684ab45",
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@@ -981,7 +989,7 @@
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   {
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-   "id": "6fa982ac",
+   "id": "ac371b5c",
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@@ -993,7 +1001,7 @@
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   {
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-   "id": "c491c9c5",
+   "id": "8dbfe230",
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@@ -1008,7 +1016,7 @@
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   {
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-   "id": "45521d36",
+   "id": "7244f7f3",
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@@ -1020,7 +1028,7 @@
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   {
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+   "id": "ffb80d86",
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@@ -1032,7 +1040,7 @@
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   {
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+   "id": "6f15ef23",
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@@ -1044,7 +1052,7 @@
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+   "id": "1734d532",
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@@ -1056,7 +1064,7 @@
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+   "id": "8c013e25",
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@@ -1066,7 +1074,7 @@
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@@ -1078,7 +1086,7 @@
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@@ -1088,7 +1096,7 @@
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@@ -1100,7 +1108,7 @@
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@@ -1121,7 +1129,7 @@
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+   "id": "0685fdd2",
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@@ -1133,7 +1141,7 @@
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@@ -1145,7 +1153,7 @@
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@@ -1155,7 +1163,7 @@
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@@ -1167,7 +1175,7 @@
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@@ -1178,7 +1186,7 @@
   {
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    "execution_count": 1,
-   "id": "96bfacee",
+   "id": "72fa0f44",
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@@ -1197,7 +1205,7 @@
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+   "id": "78884bc6",
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@@ -1208,7 +1216,7 @@
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+   "id": "f13d7286",
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@@ -1220,7 +1228,7 @@
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-   "id": "e4f9a39e",
+   "id": "443739d9",
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@@ -1230,7 +1238,7 @@
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-   "id": "d7862e63",
+   "id": "48b45da1",
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@@ -1242,7 +1250,7 @@
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-   "id": "125aa92f",
+   "id": "81e7fd8f",
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@@ -1255,7 +1263,7 @@
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-   "id": "4191307d",
+   "id": "824bbfa1",
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@@ -1267,7 +1275,7 @@
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-   "id": "2bde847d",
+   "id": "42d2716e",
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@@ -1279,7 +1287,7 @@
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-   "id": "83266d60",
+   "id": "f27855c1",
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@@ -1296,7 +1304,7 @@
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-   "id": "c5a7fbff",
+   "id": "d4fe531f",
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@@ -1308,7 +1316,7 @@
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+   "id": "aba8f666",
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@@ -1320,7 +1328,7 @@
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+   "id": "404c698a",
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@@ -1330,7 +1338,7 @@
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-   "id": "c3c09fb8",
+   "id": "2c73032a",
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@@ -1342,7 +1350,7 @@
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+   "id": "95a71a82",
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@@ -1352,7 +1360,7 @@
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+   "id": "c71b8e66",
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@@ -1364,7 +1372,7 @@
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+   "id": "23998633",
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@@ -1374,7 +1382,7 @@
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-   "id": "dee0077a",
+   "id": "0708e562",
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@@ -1386,7 +1394,7 @@
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@@ -1396,7 +1404,7 @@
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@@ -1408,7 +1416,7 @@
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@@ -1420,7 +1428,7 @@
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@@ -1430,7 +1438,7 @@
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@@ -1442,7 +1450,7 @@
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@@ -1452,7 +1460,7 @@
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@@ -1464,7 +1472,7 @@
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@@ -1482,7 +1490,7 @@
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@@ -1494,7 +1502,7 @@
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@@ -1506,7 +1514,7 @@
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@@ -1516,7 +1524,7 @@
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@@ -1528,7 +1536,7 @@
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@@ -1539,7 +1547,7 @@
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@@ -1558,7 +1566,7 @@
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@@ -1574,7 +1582,7 @@
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@@ -1587,7 +1595,7 @@
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@@ -1599,7 +1607,7 @@
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@@ -1609,7 +1617,7 @@
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@@ -1621,7 +1629,7 @@
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@@ -1631,7 +1639,7 @@
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@@ -1643,7 +1651,7 @@
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@@ -1653,7 +1661,7 @@
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@@ -1665,7 +1673,7 @@
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@@ -1677,7 +1685,7 @@
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@@ -1689,7 +1697,7 @@
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@@ -1699,7 +1707,7 @@
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@@ -1711,7 +1719,7 @@
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@@ -1721,7 +1729,7 @@
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@@ -1733,7 +1741,7 @@
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@@ -1743,7 +1751,7 @@
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@@ -1755,7 +1763,7 @@
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@@ -1765,7 +1773,7 @@
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@@ -1777,7 +1785,7 @@
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@@ -1787,7 +1795,7 @@
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@@ -1799,7 +1807,7 @@
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@@ -1810,7 +1818,7 @@
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@@ -1822,7 +1830,7 @@
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@@ -1834,7 +1842,7 @@
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@@ -1847,7 +1855,7 @@
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@@ -1857,7 +1865,7 @@
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@@ -1869,7 +1877,7 @@
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@@ -1879,7 +1887,7 @@
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@@ -1891,7 +1899,7 @@
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@@ -1901,7 +1909,7 @@
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@@ -1917,7 +1925,7 @@
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@@ -1934,7 +1942,7 @@
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@@ -1946,7 +1954,7 @@
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@@ -1959,7 +1967,7 @@
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@@ -1972,7 +1980,7 @@
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@@ -1984,7 +1992,7 @@
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@@ -1994,7 +2002,7 @@
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@@ -2006,7 +2014,7 @@
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@@ -2021,7 +2029,7 @@
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@@ -2036,7 +2044,7 @@
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@@ -2048,7 +2056,7 @@
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@@ -2062,7 +2070,7 @@
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@@ -2074,7 +2082,7 @@
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@@ -2090,7 +2098,7 @@
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@@ -2106,7 +2114,7 @@
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@@ -2118,7 +2126,7 @@
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@@ -2128,7 +2136,7 @@
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@@ -2140,7 +2148,7 @@
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@@ -2150,7 +2158,7 @@
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@@ -2162,7 +2170,7 @@
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@@ -2172,7 +2180,7 @@
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@@ -2184,7 +2192,7 @@
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@@ -2200,7 +2208,7 @@
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@@ -2212,7 +2220,7 @@
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@@ -2224,7 +2232,7 @@
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@@ -2234,7 +2242,7 @@
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@@ -2246,7 +2254,7 @@
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@@ -2256,7 +2264,7 @@
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@@ -2272,7 +2280,7 @@
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@@ -2284,7 +2292,7 @@
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@@ -2296,7 +2304,7 @@
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@@ -2308,7 +2316,7 @@
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@@ -2320,7 +2328,7 @@
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@@ -2332,7 +2340,7 @@
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@@ -2342,7 +2350,7 @@
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@@ -2358,7 +2366,7 @@
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@@ -2370,7 +2378,7 @@
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@@ -2382,7 +2390,7 @@
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@@ -2392,7 +2400,7 @@
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@@ -2404,7 +2412,7 @@
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@@ -2418,7 +2426,7 @@
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@@ -2436,7 +2444,7 @@
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@@ -2509,7 +2517,7 @@
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@@ -2519,7 +2527,7 @@
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@@ -2537,7 +2545,7 @@
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@@ -2554,7 +2562,7 @@
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@@ -2566,7 +2574,7 @@
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@@ -2576,7 +2584,7 @@
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@@ -2588,7 +2596,7 @@
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@@ -2604,7 +2612,7 @@
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@@ -2616,7 +2624,7 @@
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@@ -2628,7 +2636,7 @@
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@@ -2639,7 +2647,7 @@
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@@ -2651,7 +2659,7 @@
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@@ -2664,7 +2672,7 @@
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@@ -2676,7 +2684,7 @@
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@@ -2686,7 +2694,7 @@
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@@ -2698,7 +2706,7 @@
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-   "id": "2cb74c95",
+   "id": "6863edaa",
    "metadata": {
     "editable": true
    },
@@ -2710,7 +2718,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6f25a15d",
+   "id": "569b5a62",
    "metadata": {
     "editable": true
    },
@@ -2722,7 +2730,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "980266d5",
+   "id": "88775a53",
    "metadata": {
     "editable": true
    },
@@ -2732,7 +2740,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "70bce478",
+   "id": "11852c41",
    "metadata": {
     "editable": true
    },
@@ -2744,7 +2752,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6d265593",
+   "id": "4e2e26a9",
    "metadata": {
     "editable": true
    },
@@ -2760,7 +2768,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "dbd4e2a3",
+   "id": "25da37b5",
    "metadata": {
     "editable": true
    },
@@ -2772,7 +2780,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "09d2cf31",
+   "id": "4094b188",
    "metadata": {
     "editable": true
    },
@@ -2782,7 +2790,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f79ab8f7",
+   "id": "99f40072",
    "metadata": {
     "editable": true
    },
@@ -2794,7 +2802,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9c08c538",
+   "id": "a93180cb",
    "metadata": {
     "editable": true
    },
@@ -2804,7 +2812,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a2f6c044",
+   "id": "312c8e22",
    "metadata": {
     "editable": true
    },
@@ -2816,7 +2824,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a09f4e04",
+   "id": "4db8065c",
    "metadata": {
     "editable": true
    },
@@ -2828,7 +2836,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6a92eb7a",
+   "id": "316b7cc7",
    "metadata": {
     "editable": true
    },
@@ -2841,7 +2849,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8fe089f9",
+   "id": "8ef16e76",
    "metadata": {
     "editable": true
    },
@@ -2851,7 +2859,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a62a5291",
+   "id": "85a0f70d",
    "metadata": {
     "editable": true
    },
@@ -2863,7 +2871,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "435fd697",
+   "id": "108db06e",
    "metadata": {
     "editable": true
    },
@@ -2873,7 +2881,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "fa2bd02f",
+   "id": "2922e5c6",
    "metadata": {
     "editable": true
    },
@@ -2885,7 +2893,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b809a430",
+   "id": "cb6f6fe5",
    "metadata": {
     "editable": true
    },
@@ -2896,7 +2904,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8d9a8843",
+   "id": "3a0d272d",
    "metadata": {
     "editable": true
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@@ -2908,7 +2916,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4ac52a1d",
+   "id": "70a6cf5c",
    "metadata": {
     "editable": true
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@@ -2918,7 +2926,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f146f084",
+   "id": "a862fb73",
    "metadata": {
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@@ -2930,7 +2938,7 @@
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   {
    "cell_type": "markdown",
-   "id": "5152d124",
+   "id": "703fa2c1",
    "metadata": {
     "editable": true
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@@ -2940,7 +2948,7 @@
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   {
    "cell_type": "markdown",
-   "id": "ac1cc726",
+   "id": "2032458a",
    "metadata": {
     "editable": true
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@@ -2952,7 +2960,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "301bfbae",
+   "id": "97d8acd7",
    "metadata": {
     "editable": true
    },
@@ -2964,7 +2972,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "0f8342ca",
+   "id": "972e5301",
    "metadata": {
     "editable": true
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@@ -2976,7 +2984,7 @@
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   {
    "cell_type": "markdown",
-   "id": "3c0e1892",
+   "id": "ba8f5955",
    "metadata": {
     "editable": true
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@@ -2986,7 +2994,7 @@
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   {
    "cell_type": "markdown",
-   "id": "1fd466c4",
+   "id": "3ac41463",
    "metadata": {
     "editable": true
    },
@@ -2998,7 +3006,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "96a66261",
+   "id": "ab92a69c",
    "metadata": {
     "editable": true
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@@ -3008,7 +3016,7 @@
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   {
    "cell_type": "markdown",
-   "id": "48fec0f6",
+   "id": "8224b6f2",
    "metadata": {
     "editable": true
    },
@@ -3020,7 +3028,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "0c74d22b",
+   "id": "b55a566b",
    "metadata": {
     "editable": true
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@@ -3032,7 +3040,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "0c854481",
+   "id": "cb5f687e",
    "metadata": {
     "editable": true
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@@ -3044,7 +3052,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f10bb50d",
+   "id": "6d8361e8",
    "metadata": {
     "editable": true
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@@ -3054,7 +3062,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "76a5d55f",
+   "id": "ccfb7fa8",
    "metadata": {
     "editable": true
    },
@@ -3066,7 +3074,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e5f00732",
+   "id": "20fd0aa3",
    "metadata": {
     "editable": true
    },
@@ -3076,7 +3084,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "afdef373",
+   "id": "6bca7f99",
    "metadata": {
     "editable": true
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@@ -3089,7 +3097,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d52eee8a",
+   "id": "430e26d8",
    "metadata": {
     "editable": true
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@@ -3101,7 +3109,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "38b3bf6d",
+   "id": "ced71f83",
    "metadata": {
     "editable": true
    },
@@ -3111,7 +3119,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f6068eca",
+   "id": "ec12ee1a",
    "metadata": {
     "editable": true
    },
@@ -3123,7 +3131,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "71ee9ceb",
+   "id": "f46fe24d",
    "metadata": {
     "editable": true
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@@ -3133,7 +3141,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5c8a4ccd",
+   "id": "af8f924d",
    "metadata": {
     "editable": true
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@@ -3145,7 +3153,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "02025483",
+   "id": "4aeb6140",
    "metadata": {
     "editable": true
    },
@@ -3155,7 +3163,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c6619121",
+   "id": "0bc2f26c",
    "metadata": {
     "editable": true
    },
@@ -3167,7 +3175,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "050f3fcc",
+   "id": "7eafd358",
    "metadata": {
     "editable": true
    },
@@ -3177,7 +3185,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "06a24ad2",
+   "id": "548f58f6",
    "metadata": {
     "editable": true
    },
@@ -3189,7 +3197,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4274918f",
+   "id": "4c38514a",
    "metadata": {
     "editable": true
    },
@@ -3201,7 +3209,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "56d9f66f",
+   "id": "06303245",
    "metadata": {
     "editable": true
    },
@@ -3211,7 +3219,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "042c5edd",
+   "id": "ed0c0029",
    "metadata": {
     "editable": true
    },
@@ -3223,7 +3231,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ce337d30",
+   "id": "93df389e",
    "metadata": {
     "editable": true
    },
@@ -3236,7 +3244,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "53b17e8e",
+   "id": "5df18704",
    "metadata": {
     "editable": true
    },
@@ -3250,7 +3258,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b6759476",
+   "id": "ae3765be",
    "metadata": {
     "editable": true
    },
@@ -3262,7 +3270,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "22d35cab",
+   "id": "dd8f7882",
    "metadata": {
     "editable": true
    },
@@ -3272,7 +3280,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3869fd5f",
+   "id": "f204fdd7",
    "metadata": {
     "editable": true
    },
@@ -3284,7 +3292,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4ecac8d6",
+   "id": "c28e8401",
    "metadata": {
     "editable": true
    },
@@ -3294,7 +3302,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "33824242",
+   "id": "910c4eb1",
    "metadata": {
     "editable": true
    },
@@ -3306,7 +3314,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "905fc741",
+   "id": "efd2f948",
    "metadata": {
     "editable": true
    },
@@ -3324,7 +3332,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f81d4ba5",
+   "id": "e1eeeba2",
    "metadata": {
     "editable": true
    },
@@ -3342,7 +3350,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "36bf1dfb",
+   "id": "b5e74c11",
    "metadata": {
     "editable": true
    },
@@ -3354,7 +3362,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ef9f1e9b",
+   "id": "e129fe72",
    "metadata": {
     "editable": true
    },
@@ -3364,7 +3372,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "16944f70",
+   "id": "3879d293",
    "metadata": {
     "editable": true
    },
@@ -3376,7 +3384,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3af2849b",
+   "id": "1ea1da9d",
    "metadata": {
     "editable": true
    },
@@ -3388,7 +3396,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "aba9c751",
+   "id": "c7156e16",
    "metadata": {
     "editable": true
    },
@@ -3400,7 +3408,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e75abc21",
+   "id": "8311b4aa",
    "metadata": {
     "editable": true
    },
@@ -3410,7 +3418,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "eb71f184",
+   "id": "7bb3d820",
    "metadata": {
     "editable": true
    },
@@ -3422,7 +3430,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "31ab0d28",
+   "id": "1eeb0c00",
    "metadata": {
     "editable": true
    },
@@ -3432,7 +3440,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9ee59b2e",
+   "id": "bc7d3757",
    "metadata": {
     "editable": true
    },
@@ -3444,7 +3452,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d6fa40ac",
+   "id": "9f018cff",
    "metadata": {
     "editable": true
    },
@@ -3462,7 +3470,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "1ced4984",
+   "id": "ebde7551",
    "metadata": {
     "editable": true
    },
@@ -3472,7 +3480,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3b2fea6b",
+   "id": "f96aa8f7",
    "metadata": {
     "editable": true
    },
@@ -3490,7 +3498,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "dd703643",
+   "id": "1215d118",
    "metadata": {
     "editable": true
    },
@@ -3500,7 +3508,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d9fdc337",
+   "id": "c5f6885e",
    "metadata": {
     "editable": true
    },
@@ -3518,7 +3526,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5412dee8",
+   "id": "1dedde99",
    "metadata": {
     "editable": true
    },
@@ -3530,7 +3538,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e912e54c",
+   "id": "a182b912",
    "metadata": {
     "editable": true
    },
@@ -3542,7 +3550,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "04224d80",
+   "id": "9fcc3201",
    "metadata": {
     "editable": true
    },
@@ -3552,7 +3560,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9f08fbcc",
+   "id": "54237463",
    "metadata": {
     "editable": true
    },
@@ -3564,7 +3572,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "faa505b9",
+   "id": "dc069f5a",
    "metadata": {
     "editable": true
    },
@@ -3576,7 +3584,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ed46f21f",
+   "id": "71ba0435",
    "metadata": {
     "editable": true
    },
@@ -3586,7 +3594,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "515a4eef",
+   "id": "bd00cbe9",
    "metadata": {
     "editable": true
    },
@@ -3598,7 +3606,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "bee442d8",
+   "id": "1e7e0241",
    "metadata": {
     "editable": true
    },
@@ -3608,7 +3616,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2b2596dd",
+   "id": "e8e3697e",
    "metadata": {
     "editable": true
    },
@@ -3620,7 +3628,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "1d832dcf",
+   "id": "7d86a02b",
    "metadata": {
     "editable": true
    },
@@ -3632,7 +3640,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2f958487",
+   "id": "ff1dc46f",
    "metadata": {
     "editable": true
    },
@@ -3655,7 +3663,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8861c9ac",
+   "id": "1313e6dc",
    "metadata": {
     "editable": true
    },
@@ -3667,7 +3675,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "aff5f2e9",
+   "id": "74378773",
    "metadata": {
     "editable": true
    },
@@ -3679,7 +3687,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a12a0d0f",
+   "id": "70450254",
    "metadata": {
     "editable": true
    },
@@ -3689,7 +3697,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "eebf7ad0",
+   "id": "81a28b23",
    "metadata": {
     "editable": true
    },
@@ -3701,7 +3709,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5ac6e8cd",
+   "id": "9a733356",
    "metadata": {
     "editable": true
    },
@@ -3715,7 +3723,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "219d7967",
+   "id": "f469f486",
    "metadata": {
     "editable": true
    },
@@ -3727,7 +3735,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c5e69141",
+   "id": "7461e5e6",
    "metadata": {
     "editable": true
    },
@@ -3739,7 +3747,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5f72b173",
+   "id": "50a1b605",
    "metadata": {
     "editable": true
    },
@@ -3749,7 +3757,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "77500a39",
+   "id": "0cebce43",
    "metadata": {
     "editable": true
    },
@@ -3761,7 +3769,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6d90be80",
+   "id": "2e4405bd",
    "metadata": {
     "editable": true
    },
@@ -3773,7 +3781,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6dc431f1",
+   "id": "2920aa4e",
    "metadata": {
     "editable": true
    },
@@ -3783,7 +3791,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "bc54103e",
+   "id": "bc4357b0",
    "metadata": {
     "editable": true
    },
@@ -3795,7 +3803,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8a08a83e",
+   "id": "d9b66569",
    "metadata": {
     "editable": true
    },
diff --git a/doc/src/week41/week41.do.txt b/doc/src/week41/week41.do.txt
index 701fb667d..2dae7add5 100644
--- a/doc/src/week41/week41.do.txt
+++ b/doc/src/week41/week41.do.txt
@@ -10,17 +10,21 @@ DATE: Week 41
 ===== Material for the lecture on Monday October 6, 2025 =====
 o Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model.
 o Building our own Feed-forward Neural Network, getting started
-#  * Video of lecture notes at URL:"https://youtu.be/pMRUbf9E-gM"
-#  * Whiteboard notes at URL:"https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2024/NotesOctober7.pdf"
-!bblock  Readings and Videos:
+#  * Video of lecture notes at URL:""
+#  * Whiteboard notes at URL:"https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2025/FYSSTKweek41.pdf"
+
+
+!split
+===== Readings and Videos: =====
+!bblock  
 o These lecture notes
 o For neural networks we recommend Goodfellow et al chapters 6 and 7.
 o Rashkca et al., chapter 11, jupyter-notebook sent separately, from "GitHub":"https://github.com/rasbt/machine-learning-book"
-o  Neural Networks demystified at URL:"https://www.youtube.com/watch?v=bxe2T-V8XRs&list=PLiaHhY2iBX9hdHaRr6b7XevZtgZRa1PoU&ab_channel=WelchLabs"
+o Neural Networks demystified at URL:"https://www.youtube.com/watch?v=bxe2T-V8XRs&list=PLiaHhY2iBX9hdHaRr6b7XevZtgZRa1PoU&ab_channel=WelchLabs"
 o Building Neural Networks from scratch at URL:"https://www.youtube.com/watch?v=Wo5dMEP_BbI&list=PLQVvvaa0QuDcjD5BAw2DxE6OF2tius3V3&ab_channel=sentdex"
 o Video on Neural Networks at URL:"https://www.youtube.com/watch?v=CqOfi41LfDw"
 o Video on the back propagation algorithm at URL:"https://www.youtube.com/watch?v=Ilg3gGewQ5U"
-We also  recommend Michael Nielsen's intuitive approach to the neural networks and the universal approximation theorem, see the slides at URL:"http://neuralnetworksanddeeplearning.com/chap4.html".
+o We also  recommend Michael Nielsen's intuitive approach to the neural networks and the universal approximation theorem, see the slides at URL:"http://neuralnetworksanddeeplearning.com/chap4.html".
 !eblock
 
 !split
@@ -28,7 +32,6 @@ We also  recommend Michael Nielsen's intuitive approach to the neural networks a
 
 !bblock Two recent books online
 o "The Modern Mathematics of Deep Learning, by Julius Berner, Philipp Grohs, Gitta Kutyniok, Philipp Petersen":"https://arxiv.org/abs/2105.04026", published as "Mathematical Aspects of Deep Learning, pp. 1-111. Cambridge University Press, 2022":"https://doi.org/10.1017/9781009025096.002"
-
 o "Mathematical Introduction to Deep Learning: Methods, Implementations, and Theory, Arnulf Jentzen, Benno Kuckuck, Philippe von Wurstemberger":"https://doi.org/10.48550/arXiv.2310.20360"
 !eblock
 
@@ -36,14 +39,15 @@ o "Mathematical Introduction to Deep Learning: Methods, Implementations, and The
 !split
 ===== Reminder on books with hands-on material and codes =====
 !bblock
-* "Sebastian Rashcka et al, Machine learning with Sickit-Learn and PyTorch":"https://sebastianraschka.com/blog/2022/ml-pytorch-book.html"
+"Sebastian Rashcka et al, Machine learning with Sickit-Learn and PyTorch":"https://sebastianraschka.com/blog/2022/ml-pytorch-book.html"
 !eblock
 
 
 !split
 ===== Lab sessions on Tuesday and Wednesday =====
 
-o Getting started with coding neural network. The exercises this week aim at setting up the feed-forward part of a neural network.
+Aim: Getting started with coding neural network. The exercises this
+week aim at setting up the feed-forward part of a neural network.