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Morten Hjorth-Jensen
2023-06-01 18:58:29 +02:00
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doc/pub/week41/html/._week41-bs000.html
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@@ -292,7 +292,7 @@ MathJax.Hub.Config({
</center>
<br>
<center>
<h4>Oct 20, 2022</h4>
<h4>Week 41</h4>
</center> <!-- date -->
<br>
@@ -331,7 +331,7 @@ MathJax.Hub.Config({
</footer>
-->
<center style="font-size:80%">
<!-- copyright --> &copy; 1999-2022, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license
<!-- copyright --> &copy; 1999-2023, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license
</center>
</body>
</html>
doc/pub/week41/html/._week41-bs001.html
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@@ -277,17 +277,11 @@ MathJax.Hub.Config({
<h2 id="plan-for-week-41" class="anchor">Plan for week 41 </h2>
<ul>
<li> Thursday: Building our own Feed-forward Neural Network and discussion of project 2.</li>
<ul>
<li> <a href="https://youtu.be/yzbxJI6LgL0" target="_self">Video of lecture</a></li>
</ul>
<li> Friday: Playing around with our own Feed-forward Neural Network and introduction to TensorFlow. Solving differential equations with neural networks.</li>
<ul>
<li> "Video of lecture":"https://youtu.be/CPj4mh7M9no</li>
</ul>
<li> Building our own Feed-forward Neural Network and discussion of project 2.</li>
<li> Playing around with our own Feed-forward Neural Network and introduction to TensorFlow. Solving differential equations with neural networks.</li>
</ul>
<p>"
Reading suggestions for both days: These notes, <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/Textbooks/TensorflowML.pdf" target="_self">Aurelien Geron's chapters 10-11</a>.
Reading suggestions: These notes, <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/Textbooks/TensorflowML.pdf" target="_self">Aurelien Geron's chapters 10-11</a>.
For a more in depth discussion on neural networks we recommend Goodfellow et al chapters 6 and 7. Bishop's chapter 5 on Neural Networks is an additional good read.
</p>
doc/pub/week41/html/week41-bs.html
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@@ -292,7 +292,7 @@ MathJax.Hub.Config({
</center>
<br>
<center>
<h4>Oct 20, 2022</h4>
<h4>Week 41</h4>
</center> <!-- date -->
<br>
@@ -331,7 +331,7 @@ MathJax.Hub.Config({
</footer>
-->
<center style="font-size:80%">
<!-- copyright --> &copy; 1999-2022, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license
<!-- copyright --> &copy; 1999-2023, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license
</center>
</body>
</html>
doc/pub/week41/html/week41-reveal.html
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@@ -184,13 +184,13 @@ MathJax.Hub.Config({
</center>
<br>
<center>
<h4>Oct 20, 2022</h4>
<h4>Week 41</h4>
</center> <!-- date -->
<br>
<center style="font-size:80%">
<!-- copyright --> &copy; 1999-2022, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license
<!-- copyright --> &copy; 1999-2023, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license
</center>
</section>
@@ -198,22 +198,12 @@ MathJax.Hub.Config({
<h2 id="plan-for-week-41">Plan for week 41 </h2>
<ul>
<p><li> Thursday: Building our own Feed-forward Neural Network and discussion of project 2.</li>
<ul>
<p><li> <a href="https://youtu.be/yzbxJI6LgL0" target="_blank">Video of lecture</a></li>
</ul>
<p>
<p><li> Friday: Playing around with our own Feed-forward Neural Network and introduction to TensorFlow. Solving differential equations with neural networks.</li>
<ul>
<p><li> "Video of lecture":"https://youtu.be/CPj4mh7M9no</li>
</ul>
<p>
<p><li> Building our own Feed-forward Neural Network and discussion of project 2.</li>
<p><li> Playing around with our own Feed-forward Neural Network and introduction to TensorFlow. Solving differential equations with neural networks.</li>
</ul>
<p>
<p>"
Reading suggestions for both days: These notes, <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/Textbooks/TensorflowML.pdf" target="_blank">Aurelien Geron's chapters 10-11</a>.
Reading suggestions: These notes, <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/Textbooks/TensorflowML.pdf" target="_blank">Aurelien Geron's chapters 10-11</a>.
For a more in depth discussion on neural networks we recommend Goodfellow et al chapters 6 and 7. Bishop's chapter 5 on Neural Networks is an additional good read.
</p>
</section>
doc/pub/week41/html/week41-solarized.html
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@@ -242,7 +242,7 @@ MathJax.Hub.Config({
</center>
<br>
<center>
<h4>Oct 20, 2022</h4>
<h4>Week 41</h4>
</center> <!-- date -->
<br>
@@ -250,17 +250,11 @@ MathJax.Hub.Config({
<h2 id="plan-for-week-41">Plan for week 41 </h2>
<ul>
<li> Thursday: Building our own Feed-forward Neural Network and discussion of project 2.</li>
<ul>
<li> <a href="https://youtu.be/yzbxJI6LgL0" target="_blank">Video of lecture</a></li>
</ul>
<li> Friday: Playing around with our own Feed-forward Neural Network and introduction to TensorFlow. Solving differential equations with neural networks.</li>
<ul>
<li> "Video of lecture":"https://youtu.be/CPj4mh7M9no</li>
</ul>
<li> Building our own Feed-forward Neural Network and discussion of project 2.</li>
<li> Playing around with our own Feed-forward Neural Network and introduction to TensorFlow. Solving differential equations with neural networks.</li>
</ul>
<p>"
Reading suggestions for both days: These notes, <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/Textbooks/TensorflowML.pdf" target="_blank">Aurelien Geron's chapters 10-11</a>.
Reading suggestions: These notes, <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/Textbooks/TensorflowML.pdf" target="_blank">Aurelien Geron's chapters 10-11</a>.
For a more in depth discussion on neural networks we recommend Goodfellow et al chapters 6 and 7. Bishop's chapter 5 on Neural Networks is an additional good read.
</p>
@@ -2695,7 +2689,7 @@ features).
<!-- ------------------- end of main content --------------- -->
<center style="font-size:80%">
<!-- copyright --> &copy; 1999-2022, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license
<!-- copyright --> &copy; 1999-2023, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license
</center>
</body>
</html>
doc/pub/week41/html/week41.html
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@@ -319,7 +319,7 @@ MathJax.Hub.Config({
</center>
<br>
<center>
<h4>Oct 20, 2022</h4>
<h4>Week 41</h4>
</center> <!-- date -->
<br>
@@ -327,17 +327,11 @@ MathJax.Hub.Config({
<h2 id="plan-for-week-41">Plan for week 41 </h2>
<ul>
<li> Thursday: Building our own Feed-forward Neural Network and discussion of project 2.</li>
<ul>
<li> <a href="https://youtu.be/yzbxJI6LgL0" target="_blank">Video of lecture</a></li>
</ul>
<li> Friday: Playing around with our own Feed-forward Neural Network and introduction to TensorFlow. Solving differential equations with neural networks.</li>
<ul>
<li> "Video of lecture":"https://youtu.be/CPj4mh7M9no</li>
</ul>
<li> Building our own Feed-forward Neural Network and discussion of project 2.</li>
<li> Playing around with our own Feed-forward Neural Network and introduction to TensorFlow. Solving differential equations with neural networks.</li>
</ul>
<p>"
Reading suggestions for both days: These notes, <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/Textbooks/TensorflowML.pdf" target="_blank">Aurelien Geron's chapters 10-11</a>.
Reading suggestions: These notes, <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/Textbooks/TensorflowML.pdf" target="_blank">Aurelien Geron's chapters 10-11</a>.
For a more in depth discussion on neural networks we recommend Goodfellow et al chapters 6 and 7. Bishop's chapter 5 on Neural Networks is an additional good read.
</p>
@@ -2772,7 +2766,7 @@ features).
<!-- ------------------- end of main content --------------- -->
<center style="font-size:80%">
<!-- copyright --> &copy; 1999-2022, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license
<!-- copyright --> &copy; 1999-2023, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license
</center>
</body>
</html>
doc/pub/week41/ipynb/ipynb-week41-src.tar.gz
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doc/pub/week41/ipynb/week41.ipynb
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doc/src/week41/week41.do.txt
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@@ -1,17 +1,15 @@
TITLE: Week 41 Constructing a Neural Network code, Tensor flow and start Convolutional Neural Networks
AUTHOR: Morten Hjorth-Jensen {copyright, 1999-present|CC BY-NC} at Department of Physics, University of Oslo & Department of Physics and Astronomy and Facility for Rare Isotope Beams, Michigan State University
DATE: today
DATE: Week 41
!split
===== Plan for week 41 =====
* Thursday: Building our own Feed-forward Neural Network and discussion of project 2.
* "Video of lecture":"https://youtu.be/yzbxJI6LgL0"
* Friday: Playing around with our own Feed-forward Neural Network and introduction to TensorFlow. Solving differential equations with neural networks.
* "Video of lecture":"https://youtu.be/CPj4mh7M9no
* Building our own Feed-forward Neural Network and discussion of project 2.
* Playing around with our own Feed-forward Neural Network and introduction to TensorFlow. Solving differential equations with neural networks.
"
Reading suggestions for both days: These notes, "Aurelien Geron's chapters 10-11":"https://github.com/CompPhysics/MachineLearning/blob/master/doc/Textbooks/TensorflowML.pdf".
Reading suggestions: These notes, "Aurelien Geron's chapters 10-11":"https://github.com/CompPhysics/MachineLearning/blob/master/doc/Textbooks/TensorflowML.pdf".
For a more in depth discussion on neural networks we recommend Goodfellow et al chapters 6 and 7. Bishop's chapter 5 on Neural Networks is an additional good read.
!split