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setting up week 40

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mhjensen
2020-09-27 21:56:50 +02:00
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doc/pub/week40/ipynb/ipynb-week40-src.tar.gz
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doc/pub/week40/ipynb/week40.ipynb
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"<!-- Author: --> \n",
"**Morten Hjorth-Jensen**, Department of Physics, University of Oslo and Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University\n",
"\n",
"Date: **Sep 16, 2020**\n",
"Date: **Sep 27, 2020**\n",
"\n",
"Copyright 1999-2020, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license\n",
"\n",
"\n",
"\n",
"\n",
"## Plan for week 40\n",
"\n",
"* Thursday: Stochastic Gradient descent with examples and automatic differeantion and begin Neural Networks \n",
"\n",
"* Friday: Neural Networks, setting up the basic steps\n",
"\n",
"Reading suggestions for both days: [Aurelien Geron's chapter 10](https://github.com/CompPhysics/MachineLearning/blob/master/doc/Textbooks/TensorflowML.pdf) and Hastie et al chapter 11.\n",
"\n",
"## Overview video for week 40\n",
"\n",
"[Overview Video, fro Stochastic Gradient methods to Neural Networks](https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h20/forelesningsvideoer/OverarchingAimsWeek40.mp4?vrtx=view-as-webpage)\n",
"\n",
"\n",
"\n",
"## Neural networks\n",
"\n",
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],
"metadata": {},
"nbformat": 4,
"nbformat_minor": 2
"nbformat_minor": 4
}
doc/src/week40/week40.do.txt
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DATE: today
!split
===== Plan for week 40 =====
* Thursday: Stochastic Gradient descent with examples and automatic differeantion and begin Neural Networks
* Friday: Neural Networks, setting up the basic steps
Reading suggestions for both days: "Aurelien Geron's chapter 10":"https://github.com/CompPhysics/MachineLearning/blob/master/doc/Textbooks/TensorflowML.pdf" and Hastie et al chapter 11.
!split
===== Overview video for week 40 =====
"Overview Video, fro Stochastic Gradient methods to Neural Networks":"https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h20/forelesningsvideoer/OverarchingAimsWeek40.mp4?vrtx=view-as-webpage"
!split
===== Neural networks =====
@@ -2452,3 +2467,8 @@ Here we list some of the important limitations of supervised neural network base
Some of these remarks are particular to DNNs, others are shared by all supervised learning methods. This motivates the use of unsupervised methods which in part circumvent these problems.