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Morten Hjorth-Jensen
2022-10-19 06:53:30 +02:00
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commit fb269f5bfc
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doc/LectureNotes/schedule.md
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@@ -114,7 +114,7 @@ For the reading assignments we use the following abbreviations:
- Lecture Thursday: Deep learning and Neural Networks, developing a code for Neural Networks
- Video of Lecture at https://youtu.be/yzbxJI6LgL0
- Lecture Friday: Tensorflow and the mathematics of neural network
- Video of Lecture at
- Video of Lecture at https://youtu.be/CPj4mh7M9no
- Reading recommendations:
- See lecture notes for week 41 at https://compphysics.github.io/MachineLearning/doc/web/course.html.
- For neural networks we recommend Goodfellow et al chapters 6 and 7. For CNNs, see Goodfellow et al chapter 9. chapter 11 and 12 on practicalities and applications
doc/src/week41/week41.do.txt
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@@ -9,7 +9,8 @@ DATE: today
* 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
"
Reading suggestions for both days: 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.