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‎doc/pub/week45/html/._week45-bs001.html‎

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<!-- subsequent paragraphs come in larger fonts, so start with a paragraph -->
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<ol>
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<li> Convolutional Neural Networks, codes and examples (TensorFlow and Pytorch implementations)</li>
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<li> Readings and Videos:
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<!-- o These lecture notes at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/pub/week45/ipynb/week45.ipynb" target="_self"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/pub/week45/ipynb/week45.ipynb</tt></a> -->
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<!-- * <a href="https://youtu.be/z0x-vgyAZUk" target="_self">Video of lecture</a> -->
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<!-- * <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2023/NotesNov9.pdf" target="_self">Whiteboard notes</a> --></li>
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<li> Readings and Videos:</li>
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<li> These lecture notes at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/pub/week45/ipynb/week45.ipynb" target="_self"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/pub/week45/ipynb/week45.ipynb</tt></a></li>
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<li> Video of lecture at <a href="https://youtu.be/dZt6Vm1wjhs" target="_self"><tt>https://youtu.be/dZt6Vm1wjhs</tt></a></li>
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<li> Whiteboard notes at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2025/FYSSTKweek45.pdf" target="_self"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2025/FYSSTKweek45.pdf</tt></a></li>
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<li> For a more in depth discussion on CNNs we recommend Goodfellow et al chapters 9. See also chapter 11 and 12 on practicalities and applications</li>
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<li> Reading suggestions for implementation of CNNs, see Raschka et al chapters 14-15 at <a href="https://github.com/rasbt/machine-learning-book" target="_self"><tt>https://github.com/rasbt/machine-learning-book</tt></a>.
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<!-- o Video on Recurrent Neural Networks from MIT at <a href="https://www.youtube.com/watch?v=SEnXr6v2ifU&ab_channel=AlexanderAmini" target="_self"><tt>https://www.youtube.com/watch?v=SEnXr6v2ifU&ab_channel=AlexanderAmini</tt></a> -->

‎doc/pub/week45/html/week45-reveal.html‎

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<p>
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<ol>
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<p><li> Convolutional Neural Networks, codes and examples (TensorFlow and Pytorch implementations)</li>
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<p><li> Readings and Videos:
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<!-- o These lecture notes at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/pub/week45/ipynb/week45.ipynb" target="_blank"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/pub/week45/ipynb/week45.ipynb</tt></a> -->
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<!-- * <a href="https://youtu.be/z0x-vgyAZUk" target="_blank">Video of lecture</a> -->
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<!-- * <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2023/NotesNov9.pdf" target="_blank">Whiteboard notes</a> --></li>
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<p><li> Readings and Videos:</li>
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<p><li> These lecture notes at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/pub/week45/ipynb/week45.ipynb" target="_blank"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/pub/week45/ipynb/week45.ipynb</tt></a></li>
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<p><li> Video of lecture at <a href="https://youtu.be/dZt6Vm1wjhs" target="_blank"><tt>https://youtu.be/dZt6Vm1wjhs</tt></a></li>
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<p><li> Whiteboard notes at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2025/FYSSTKweek45.pdf" target="_blank"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2025/FYSSTKweek45.pdf</tt></a></li>
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<p><li> For a more in depth discussion on CNNs we recommend Goodfellow et al chapters 9. See also chapter 11 and 12 on practicalities and applications</li>
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<p><li> Reading suggestions for implementation of CNNs, see Raschka et al chapters 14-15 at <a href="https://github.com/rasbt/machine-learning-book" target="_blank"><tt>https://github.com/rasbt/machine-learning-book</tt></a>.

‎doc/pub/week45/html/week45-solarized.html‎

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<p>
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<ol>
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<li> Convolutional Neural Networks, codes and examples (TensorFlow and Pytorch implementations)</li>
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<li> Readings and Videos:
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<!-- o These lecture notes at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/pub/week45/ipynb/week45.ipynb" target="_blank"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/pub/week45/ipynb/week45.ipynb</tt></a> -->
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<!-- * <a href="https://youtu.be/z0x-vgyAZUk" target="_blank">Video of lecture</a> -->
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<!-- * <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2023/NotesNov9.pdf" target="_blank">Whiteboard notes</a> --></li>
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<li> Readings and Videos:</li>
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<li> These lecture notes at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/pub/week45/ipynb/week45.ipynb" target="_blank"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/pub/week45/ipynb/week45.ipynb</tt></a></li>
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<li> Video of lecture at <a href="https://youtu.be/dZt6Vm1wjhs" target="_blank"><tt>https://youtu.be/dZt6Vm1wjhs</tt></a></li>
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<li> Whiteboard notes at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2025/FYSSTKweek45.pdf" target="_blank"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2025/FYSSTKweek45.pdf</tt></a></li>
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<li> For a more in depth discussion on CNNs we recommend Goodfellow et al chapters 9. See also chapter 11 and 12 on practicalities and applications</li>
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<li> Reading suggestions for implementation of CNNs, see Raschka et al chapters 14-15 at <a href="https://github.com/rasbt/machine-learning-book" target="_blank"><tt>https://github.com/rasbt/machine-learning-book</tt></a>.
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<!-- o Video on Recurrent Neural Networks from MIT at <a href="https://www.youtube.com/watch?v=SEnXr6v2ifU&ab_channel=AlexanderAmini" target="_blank"><tt>https://www.youtube.com/watch?v=SEnXr6v2ifU&ab_channel=AlexanderAmini</tt></a> -->

‎doc/pub/week45/html/week45.html‎

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<ol>
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<li> Convolutional Neural Networks, codes and examples (TensorFlow and Pytorch implementations)</li>
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<li> Readings and Videos:
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<!-- o These lecture notes at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/pub/week45/ipynb/week45.ipynb" target="_blank"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/pub/week45/ipynb/week45.ipynb</tt></a> -->
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<!-- * <a href="https://youtu.be/z0x-vgyAZUk" target="_blank">Video of lecture</a> -->
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<!-- * <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2023/NotesNov9.pdf" target="_blank">Whiteboard notes</a> --></li>
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<li> Readings and Videos:</li>
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<li> These lecture notes at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/pub/week45/ipynb/week45.ipynb" target="_blank"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/pub/week45/ipynb/week45.ipynb</tt></a></li>
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<li> Video of lecture at <a href="https://youtu.be/dZt6Vm1wjhs" target="_blank"><tt>https://youtu.be/dZt6Vm1wjhs</tt></a></li>
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<li> Whiteboard notes at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2025/FYSSTKweek45.pdf" target="_blank"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2025/FYSSTKweek45.pdf</tt></a></li>
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<li> For a more in depth discussion on CNNs we recommend Goodfellow et al chapters 9. See also chapter 11 and 12 on practicalities and applications</li>
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<li> Reading suggestions for implementation of CNNs, see Raschka et al chapters 14-15 at <a href="https://github.com/rasbt/machine-learning-book" target="_blank"><tt>https://github.com/rasbt/machine-learning-book</tt></a>.
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<!-- o Video on Recurrent Neural Networks from MIT at <a href="https://www.youtube.com/watch?v=SEnXr6v2ifU&ab_channel=AlexanderAmini" target="_blank"><tt>https://www.youtube.com/watch?v=SEnXr6v2ifU&ab_channel=AlexanderAmini</tt></a> -->

‎doc/pub/week45/ipynb/ipynb-week45-src.tar.gz‎

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