diff --git a/doc/pub/week34/html/._week34-bs000.html b/doc/pub/week34/html/._week34-bs000.html
index 92b2c270b..453306eef 100644
--- a/doc/pub/week34/html/._week34-bs000.html
+++ b/doc/pub/week34/html/._week34-bs000.html
@@ -384,7 +384,7 @@ MathJax.Hub.Config({
 <center>[2] <b>Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University</b></center>
 <br>
 <p>
-<center><h4>Aug 27, 2021</h4></center> <!-- date -->
+<center><h4>Aug 28, 2021</h4></center> <!-- date -->
 <br>
 <p>
 
diff --git a/doc/pub/week34/html/._week34-bs037.html b/doc/pub/week34/html/._week34-bs037.html
index 9fa8d668c..dc8c8109e 100644
--- a/doc/pub/week34/html/._week34-bs037.html
+++ b/doc/pub/week34/html/._week34-bs037.html
@@ -367,6 +367,9 @@ MathJax.Hub.Config({
 
 <h2 id="friday-august-27" class="anchor">Friday August 27 </h2>
 
+<p>
+"Video of Lecture August 27, 2021":"https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h21/forelesningsvideoer/LectureThursdayAugust27.mp4?vrtx=view-as-webpage
+
 <p>
 <a href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h20/forelesningsvideoer/LectureAug21.mp4?vrtx=view-as-webpage" target="_self">Video of Lecture from fall 2020</a>  and <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/NotesAugust21.pdf" target="_self">Handwritten notes</a>
 
diff --git a/doc/pub/week34/html/week34-bs.html b/doc/pub/week34/html/week34-bs.html
index 92b2c270b..453306eef 100644
--- a/doc/pub/week34/html/week34-bs.html
+++ b/doc/pub/week34/html/week34-bs.html
@@ -384,7 +384,7 @@ MathJax.Hub.Config({
 <center>[2] <b>Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University</b></center>
 <br>
 <p>
-<center><h4>Aug 27, 2021</h4></center> <!-- date -->
+<center><h4>Aug 28, 2021</h4></center> <!-- date -->
 <br>
 <p>
 
diff --git a/doc/pub/week34/html/week34-reveal.html b/doc/pub/week34/html/week34-reveal.html
index 07e207628..194d7a642 100644
--- a/doc/pub/week34/html/week34-reveal.html
+++ b/doc/pub/week34/html/week34-reveal.html
@@ -148,7 +148,7 @@ MathJax.Hub.Config({
 <center>[2] <b>Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University</b></center>
 <br>
 <p>&nbsp;<br>
-<center><h4>Aug 27, 2021</h4></center> <!-- date -->
+<center><h4>Aug 28, 2021</h4></center> <!-- date -->
 <br>
 <p>
 
@@ -1442,6 +1442,9 @@ For multidimensional arrays, we recommend strongly <a href="http://xarray.pydata
 <section>
 <h2 id="friday-august-27">Friday August 27 </h2>
 
+<p>
+"Video of Lecture August 27, 2021":"https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h21/forelesningsvideoer/LectureThursdayAugust27.mp4?vrtx=view-as-webpage
+
 <p>
 <a href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h20/forelesningsvideoer/LectureAug21.mp4?vrtx=view-as-webpage" target="_blank">Video of Lecture from fall 2020</a>  and <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/NotesAugust21.pdf" target="_blank">Handwritten notes</a>
 </section>
diff --git a/doc/pub/week34/html/week34-solarized.html b/doc/pub/week34/html/week34-solarized.html
index 537a3b7fa..1931daac5 100644
--- a/doc/pub/week34/html/week34-solarized.html
+++ b/doc/pub/week34/html/week34-solarized.html
@@ -300,7 +300,7 @@ MathJax.Hub.Config({
 <center>[2] <b>Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University</b></center>
 <br>
 <p>
-<center><h4>Aug 27, 2021</h4></center> <!-- date -->
+<center><h4>Aug 28, 2021</h4></center> <!-- date -->
 <br>
 <p>
 <!-- !split --><br><br><br><br><br><br><br><br><br><br>
@@ -1545,6 +1545,9 @@ For multidimensional arrays, we recommend strongly <a href="http://xarray.pydata
 
 <h2 id="friday-august-27">Friday August 27 </h2>
 
+<p>
+"Video of Lecture August 27, 2021":"https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h21/forelesningsvideoer/LectureThursdayAugust27.mp4?vrtx=view-as-webpage
+
 <p>
 <a href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h20/forelesningsvideoer/LectureAug21.mp4?vrtx=view-as-webpage" target="_blank">Video of Lecture from fall 2020</a>  and <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/NotesAugust21.pdf" target="_blank">Handwritten notes</a>
 
diff --git a/doc/pub/week34/html/week34.html b/doc/pub/week34/html/week34.html
index 808fa980d..05fd55162 100644
--- a/doc/pub/week34/html/week34.html
+++ b/doc/pub/week34/html/week34.html
@@ -305,7 +305,7 @@ MathJax.Hub.Config({
 <center>[2] <b>Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University</b></center>
 <br>
 <p>
-<center><h4>Aug 27, 2021</h4></center> <!-- date -->
+<center><h4>Aug 28, 2021</h4></center> <!-- date -->
 <br>
 <p>
 <!-- !split --><br><br><br><br><br><br><br><br><br><br>
@@ -1550,6 +1550,9 @@ For multidimensional arrays, we recommend strongly <a href="http://xarray.pydata
 
 <h2 id="friday-august-27">Friday August 27 </h2>
 
+<p>
+"Video of Lecture August 27, 2021":"https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h21/forelesningsvideoer/LectureThursdayAugust27.mp4?vrtx=view-as-webpage
+
 <p>
 <a href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h20/forelesningsvideoer/LectureAug21.mp4?vrtx=view-as-webpage" target="_blank">Video of Lecture from fall 2020</a>  and <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/NotesAugust21.pdf" target="_blank">Handwritten notes</a>
 
diff --git a/doc/pub/week34/ipynb/ipynb-week34-src.tar.gz b/doc/pub/week34/ipynb/ipynb-week34-src.tar.gz
index cf39415ef..8c95f811d 100644
Binary files a/doc/pub/week34/ipynb/ipynb-week34-src.tar.gz and b/doc/pub/week34/ipynb/ipynb-week34-src.tar.gz differ
diff --git a/doc/pub/week34/ipynb/week34.ipynb b/doc/pub/week34/ipynb/week34.ipynb
index 6031333d1..ced05ff31 100644
--- a/doc/pub/week34/ipynb/week34.ipynb
+++ b/doc/pub/week34/ipynb/week34.ipynb
@@ -10,7 +10,7 @@
     "<!-- Author: -->  \n",
     "**Morten Hjorth-Jensen**, Department of Physics, University of Oslo and Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University\n",
     "\n",
-    "Date: **Aug 27, 2021**\n",
+    "Date: **Aug 28, 2021**\n",
     "\n",
     "Copyright 1999-2021, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license\n",
     "\n",
@@ -819,7 +819,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "import numpy as np"
@@ -835,7 +838,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "n = 10\n",
@@ -854,7 +860,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "import numpy as np\n",
@@ -873,7 +882,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "import numpy as np\n",
@@ -897,7 +909,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "import numpy as np\n",
@@ -919,7 +934,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "import numpy as np\n",
@@ -937,7 +955,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "import numpy as np\n",
@@ -955,7 +976,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "import numpy as np\n",
@@ -977,7 +1001,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "import numpy as np\n",
@@ -995,7 +1022,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "import numpy as np\n",
@@ -1014,7 +1044,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "import numpy as np\n",
@@ -1033,7 +1066,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "import numpy as np\n",
@@ -1053,7 +1089,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "import numpy as np\n",
@@ -1073,7 +1112,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "import numpy as np\n",
@@ -1157,7 +1199,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "# Importing various packages\n",
@@ -1180,7 +1225,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "%matplotlib inline\n",
@@ -1223,7 +1271,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "import pandas as pd\n",
@@ -1250,7 +1301,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "data_pandas = pd.DataFrame(data,index=['Frodo','Bilbo','Aragorn','Sam'])\n",
@@ -1267,7 +1321,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "display(data_pandas.loc['Aragorn'])"
@@ -1283,7 +1340,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "new_hobbit = {'First Name': [\"Peregrin\"],\n",
@@ -1306,7 +1366,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "import numpy as np\n",
@@ -1334,7 +1397,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "df.columns = ['First', 'Second', 'Third', 'Fourth', 'Fifth']\n",
@@ -1367,7 +1433,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "b = np.arange(16).reshape((4,4))\n",
@@ -1392,6 +1461,11 @@
     "\n",
     "## Friday August 27\n",
     "\n",
+    "\n",
+    "\"Video of Lecture August 27, 2021\":\"https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h21/forelesningsvideoer/LectureThursdayAugust27.mp4?vrtx=view-as-webpage\n",
+    "\n",
+    "\n",
+    "\n",
     "[Video of Lecture from fall 2020](https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h20/forelesningsvideoer/LectureAug21.mp4?vrtx=view-as-webpage)  and [Handwritten notes](https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/NotesAugust21.pdf)\n",
     "\n",
     "\n",
@@ -1458,7 +1532,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "# Importing various packages\n",
@@ -1587,7 +1664,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "import numpy as np\n",
@@ -1629,7 +1709,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "import numpy as np \n",
@@ -1802,7 +1885,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "import matplotlib.pyplot as plt\n",
@@ -2006,7 +2092,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "# Common imports\n",
@@ -2054,7 +2143,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "from pylab import plt, mpl\n",
@@ -2087,7 +2179,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "\"\"\"                                                                                                                         \n",
@@ -2115,7 +2210,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "# Read the experimental data with Pandas\n",
@@ -2157,7 +2255,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "A = Masses['A']\n",
@@ -2179,7 +2280,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "# Now we set up the design matrix X\n",
@@ -2201,7 +2305,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "clf = skl.LinearRegression().fit(X, Energies)\n",
@@ -2219,7 +2326,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "# The mean squared error                               \n",
@@ -2256,7 +2366,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "\n",
@@ -2304,7 +2417,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "from sklearn.neural_network import MLPRegressor\n",
@@ -2716,161 +2832,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>1</th>\n",
-       "      <th>A</th>\n",
-       "      <th>A^(2/3)</th>\n",
-       "      <th>A^(-1/3)</th>\n",
-       "      <th>1/A</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>A</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>1.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>1.587401</td>\n",
-       "      <td>0.793701</td>\n",
-       "      <td>0.500000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.080084</td>\n",
-       "      <td>0.693361</td>\n",
-       "      <td>0.333333</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>1.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>2.519842</td>\n",
-       "      <td>0.629961</td>\n",
-       "      <td>0.250000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>1.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>2.924018</td>\n",
-       "      <td>0.584804</td>\n",
-       "      <td>0.200000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>264</th>\n",
-       "      <td>1.0</td>\n",
-       "      <td>264.0</td>\n",
-       "      <td>41.153106</td>\n",
-       "      <td>0.155883</td>\n",
-       "      <td>0.003788</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>265</th>\n",
-       "      <td>1.0</td>\n",
-       "      <td>265.0</td>\n",
-       "      <td>41.256962</td>\n",
-       "      <td>0.155687</td>\n",
-       "      <td>0.003774</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>266</th>\n",
-       "      <td>1.0</td>\n",
-       "      <td>266.0</td>\n",
-       "      <td>41.360688</td>\n",
-       "      <td>0.155491</td>\n",
-       "      <td>0.003759</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>269</th>\n",
-       "      <td>1.0</td>\n",
-       "      <td>269.0</td>\n",
-       "      <td>41.671089</td>\n",
-       "      <td>0.154911</td>\n",
-       "      <td>0.003717</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>270</th>\n",
-       "      <td>1.0</td>\n",
-       "      <td>270.0</td>\n",
-       "      <td>41.774300</td>\n",
-       "      <td>0.154720</td>\n",
-       "      <td>0.003704</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>267 rows × 5 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "       1      A    A^(2/3)  A^(-1/3)       1/A\n",
-       "A                                             \n",
-       "1    1.0    1.0   1.000000  1.000000  1.000000\n",
-       "2    1.0    2.0   1.587401  0.793701  0.500000\n",
-       "3    1.0    3.0   2.080084  0.693361  0.333333\n",
-       "4    1.0    4.0   2.519842  0.629961  0.250000\n",
-       "5    1.0    5.0   2.924018  0.584804  0.200000\n",
-       "..   ...    ...        ...       ...       ...\n",
-       "264  1.0  264.0  41.153106  0.155883  0.003788\n",
-       "265  1.0  265.0  41.256962  0.155687  0.003774\n",
-       "266  1.0  266.0  41.360688  0.155491  0.003759\n",
-       "269  1.0  269.0  41.671089  0.154911  0.003717\n",
-       "270  1.0  270.0  41.774300  0.154720  0.003704\n",
-       "\n",
-       "[267 rows x 5 columns]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
+   "outputs": [],
    "source": [
     "# Common imports\n",
     "import numpy as np\n",
@@ -3371,8 +3338,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "# matrix inversion to find beta\n",
@@ -3390,8 +3360,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "fit = np.linalg.lstsq(X, Energies, rcond =None)[0]\n",
@@ -3407,22 +3380,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
+   "outputs": [],
    "source": [
     "Masses['Eapprox']  = ytilde\n",
     "# Generate a plot comparing the experimental with the fitted values values.\n",
@@ -3450,8 +3413,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "def R2(y_data, y_model):\n",
@@ -3467,17 +3433,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "0.9547578478889096\n"
-     ]
-    }
-   ],
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
+   "outputs": [],
    "source": [
     "print(R2(Energies,ytilde))"
    ]
@@ -3491,17 +3452,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "0.03787596148305236\n"
-     ]
-    }
-   ],
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
+   "outputs": [],
    "source": [
     "def MSE(y_data,y_model):\n",
     "    n = np.size(y_model)\n",
@@ -3519,29 +3475,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "A        \n",
-      "1    0            inf\n",
-      "2    1       1.123190\n",
-      "3    2       0.327631\n",
-      "4    6       0.344172\n",
-      "5    9       0.044402\n",
-      "               ...   \n",
-      "264  3304    0.009911\n",
-      "265  3310    0.009154\n",
-      "266  3317    0.007824\n",
-      "269  3338    0.011347\n",
-      "270  3344    0.009790\n",
-      "Name: Ebinding, Length: 267, dtype: float64\n"
-     ]
-    }
-   ],
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
+   "outputs": [],
    "source": [
     "def RelativeError(y_data,y_model):\n",
     "    return abs((y_data-y_model)/y_data)\n",
@@ -3916,7 +3855,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "# Common imports\n",
@@ -4035,7 +3977,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "import os\n",
@@ -4193,7 +4138,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "x = np.random.rand(100,1)\n",
@@ -4270,7 +4218,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "import os\n",
@@ -4371,7 +4322,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "# split in training and test data\n",
@@ -4388,7 +4342,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "scaler = StandardScaler()\n",
@@ -4416,7 +4373,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "np.random.seed()\n",
@@ -4448,25 +4408,7 @@
    ]
   }
  ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.8.5"
-  }
- },
+ "metadata": {},
  "nbformat": 4,
  "nbformat_minor": 4
 }
diff --git a/doc/src/week34/week34.do.txt b/doc/src/week34/week34.do.txt
index ad6c46f02..e8d2cd87c 100644
--- a/doc/src/week34/week34.do.txt
+++ b/doc/src/week34/week34.do.txt
@@ -1014,6 +1014,11 @@ For multidimensional arrays, we recommend strongly "xarray":"http://xarray.pydat
 !split
 ===== Friday August 27 =====
 
+
+"Video of Lecture August 27, 2021":"https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h21/forelesningsvideoer/LectureThursdayAugust27.mp4?vrtx=view-as-webpage
+
+
+
 "Video of Lecture from fall 2020":"https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h20/forelesningsvideoer/LectureAug21.mp4?vrtx=view-as-webpage"  and "Handwritten notes":"https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/NotesAugust21.pdf"