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Morten Hjorth-Jensen
2021-10-07 16:23:36 +02:00
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doc/LectureNotes/_build/.doctrees/environment.pickle
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@@ -102,10 +102,12 @@ For the reading assignments we use the following abbreviations:
### Week 40 October 4-8
- Lab Wednesday: Wrap up project 1
- 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
- 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
- For stochastic gradient descent we recommend Goodfellow et al chapter 8
### Week 41 October 11-15
- Lab Wednesday: Work on project 2
doc/LectureNotes/_build/html/schedule.html
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<h3>Week 40 October 4-8<a class="headerlink" href="#week-40-october-4-8" title="Permalink to this headline"></a></h3>
<ul class="simple">
<li><p>Lab Wednesday: Wrap up project 1</p></li>
<li><p>Lecture Thursday: Stochastic gradient descent, automatic differentiation and start discussion of feed-forward Neural Network code for regression and classification</p></li>
<li><p>Lecture Thursday: Stochastic gradient descent, automatic differentiation and start discussion of feed-forward Neural Network code for regression and classification</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/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>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>
<li><p>For neural networks we recommend Goodfellow et al chapters 6 and 7 and Bishop 5.1-5.4</p></li>
<li><p>For stochastic gradient descent we recommend Goodfellow et al chapter 8</p></li>
</ul>
</li>
</ul>
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doc/LectureNotes/schedule.md
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@@ -102,10 +102,12 @@ For the reading assignments we use the following abbreviations:
### Week 40 October 4-8
- Lab Wednesday: Wrap up project 1
- 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
- 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
- For stochastic gradient descent we recommend Goodfellow et al chapter 8
### Week 41 October 11-15
- Lab Wednesday: Work on project 2