diff --git a/README.md b/README.md
index 9f2d12dd7..30dbb0ab3 100644
--- a/README.md
+++ b/README.md
@@ -334,6 +334,7 @@ Recommended prereading: Chapters 1-2 (linear algebra) and chapter 3 (statistics)
 - Lecture Thursday: Stochastic gradient methods and start discussion of neural networks
   - Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober7.mp4?vrtx=view-as-webpage
 - Lecture Friday:  Deep Learning and Neural Networks
+  - Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober8.mp4?vrtx=view-as-webpage
 - Reading recommendations:
   - See lecture notes for week 40 at https://compphysics.github.io/MachineLearning/doc/web/course.html.
   - For neural networks we recommend Goodfellow et al chapters 6 and 7 and Bishop 5.1-5.4
diff --git a/doc/LectureNotes/_build/.doctrees/environment.pickle b/doc/LectureNotes/_build/.doctrees/environment.pickle
index e0c09b986..0a912a0a2 100644
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diff --git a/doc/LectureNotes/_build/.doctrees/schedule.doctree b/doc/LectureNotes/_build/.doctrees/schedule.doctree
index 9bcfd50b8..b8059a7e0 100644
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diff --git a/doc/LectureNotes/_build/html/_sources/schedule.md b/doc/LectureNotes/_build/html/_sources/schedule.md
index d91c45332..41568bb02 100644
--- a/doc/LectureNotes/_build/html/_sources/schedule.md
+++ b/doc/LectureNotes/_build/html/_sources/schedule.md
@@ -104,6 +104,7 @@ For the reading assignments we use the following abbreviations:
 - Lecture Thursday: Stochastic gradient descent, automatic differentiation and start discussion of  feed-forward Neural Network code for regression and classification
   - Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober7.mp4?vrtx=view-as-webpage
 - Lecture Friday:  Deep Learning and Neural Networks
+  - Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober8.mp4?vrtx=view-as-webpage 
 - Reading recommendations:
   - See lecture notes for week 40 at https://compphysics.github.io/MachineLearning/doc/web/course.html.
   - For neural networks we recommend Goodfellow et al chapters 6 and 7 and Bishop 5.1-5.4
diff --git a/doc/LectureNotes/_build/html/schedule.html b/doc/LectureNotes/_build/html/schedule.html
index 0df2c1cf7..65d532816 100644
--- a/doc/LectureNotes/_build/html/schedule.html
+++ b/doc/LectureNotes/_build/html/schedule.html
@@ -540,7 +540,11 @@
 <li><p>Video of Lecture at <a class="reference external" href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober7.mp4?vrtx=view-as-webpage">https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober7.mp4?vrtx=view-as-webpage</a></p></li>
 </ul>
 </li>
-<li><p>Lecture Friday:  Deep Learning and Neural Networks</p></li>
+<li><p>Lecture Friday:  Deep Learning and Neural Networks</p>
+<ul>
+<li><p>Video of Lecture at <a class="reference external" href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober8.mp4?vrtx=view-as-webpage">https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober8.mp4?vrtx=view-as-webpage</a></p></li>
+</ul>
+</li>
 <li><p>Reading recommendations:</p>
 <ul>
 <li><p>See lecture notes for week 40 at <a class="reference external" href="https://compphysics.github.io/MachineLearning/doc/web/course.html">https://compphysics.github.io/MachineLearning/doc/web/course.html</a>.</p></li>
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index 1322fa60b..d75361969 100644
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class=\"section-number\">12. </span>Clustering Analysis","<span class=\"section-number\">3. </span>Linear Regression","<span class=\"section-number\">14. </span>Building a Feed Forward Neural Network","<span class=\"section-number\">4. </span>Ridge and Lasso Regression","<span class=\"section-number\">5. </span>Resampling Methods","<span class=\"section-number\">6. </span>Logistic Regression","<span class=\"section-number\">8. </span>Support Vector Machines, overarching aims","<span class=\"section-number\">9. </span>Decision trees, overarching aims","<span class=\"section-number\">10. </span>Ensemble Methods: From a Single Tree to Many Trees and Extreme Boosting, Meet the Jungle of Methods","<span class=\"section-number\">11. </span>Basic ideas of the Principal Component Analysis (PCA)","<span class=\"section-number\">13. </span>Neural networks","<span class=\"section-number\">7. </span>Optimization, the central part of any Machine Learning algortithm","Content in Jupyter 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\ No newline at end of file
diff --git a/doc/LectureNotes/schedule.md b/doc/LectureNotes/schedule.md
index d91c45332..41568bb02 100644
--- a/doc/LectureNotes/schedule.md
+++ b/doc/LectureNotes/schedule.md
@@ -104,6 +104,7 @@ For the reading assignments we use the following abbreviations:
 - Lecture Thursday: Stochastic gradient descent, automatic differentiation and start discussion of  feed-forward Neural Network code for regression and classification
   - Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober7.mp4?vrtx=view-as-webpage
 - Lecture Friday:  Deep Learning and Neural Networks
+  - Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober8.mp4?vrtx=view-as-webpage 
 - Reading recommendations:
   - See lecture notes for week 40 at https://compphysics.github.io/MachineLearning/doc/web/course.html.
   - For neural networks we recommend Goodfellow et al chapters 6 and 7 and Bishop 5.1-5.4