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added update to week40

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mhjensen
2020-10-04 20:11:33 +02:00
parent 9acc24f4c1
commit 3cb9aca9ba
8 changed files with 60 additions and 46 deletions
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doc/pub/week40/html/._week40-bs000.html
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@@ -254,7 +254,7 @@ MathJax.Hub.Config({
<center>[2] <b>Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University</b></center>
<br>
<p>
<center><h4>Oct 2, 2020</h4></center> <!-- date -->
<center><h4>Oct 4, 2020</h4></center> <!-- date -->
<br>
<p>
doc/pub/week40/html/._week40-bs001.html
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@@ -239,7 +239,7 @@ MathJax.Hub.Config({
<ul>
<li> Thursday: Stochastic Gradient descent with examples and automatic differentiation and begin Neural Networks. <a href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h20/forelesningsvideoer/LectureOctober1.mp4?vrtx=view-as-webpage" target="_self">Video of Lecture</a></li>
<li> Friday: Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model</li>
<li> Friday: Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model. <a href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h20/forelesningsvideoer/LectureOctober2.mp4?vrtx=view-as-webpage" target="_self">Video of Lecture</a></li>
</ul>
Reading suggestions for both days: <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/Textbooks/TensorflowML.pdf" target="_self">Aurelien Geron's chapter 10</a> and Hastie et al chapter 11.
doc/pub/week40/html/week40-bs.html
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@@ -254,7 +254,7 @@ MathJax.Hub.Config({
<center>[2] <b>Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University</b></center>
<br>
<p>
<center><h4>Oct 2, 2020</h4></center> <!-- date -->
<center><h4>Oct 4, 2020</h4></center> <!-- date -->
<br>
<p>
doc/pub/week40/html/week40-reveal.html
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@@ -148,7 +148,7 @@ MathJax.Hub.Config({
<center>[2] <b>Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University</b></center>
<br>
<p>&nbsp;<br>
<center><h4>Oct 2, 2020</h4></center> <!-- date -->
<center><h4>Oct 4, 2020</h4></center> <!-- date -->
<br>
<p>
@@ -163,7 +163,7 @@ MathJax.Hub.Config({
<ul>
<p><li> Thursday: Stochastic Gradient descent with examples and automatic differentiation and begin Neural Networks. <a href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h20/forelesningsvideoer/LectureOctober1.mp4?vrtx=view-as-webpage" target="_blank">Video of Lecture</a></li>
<p><li> Friday: Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model</li>
<p><li> Friday: Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model. <a href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h20/forelesningsvideoer/LectureOctober2.mp4?vrtx=view-as-webpage" target="_blank">Video of Lecture</a></li>
</ul>
<p>
doc/pub/week40/html/week40-solarized.html
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@@ -186,7 +186,7 @@ MathJax.Hub.Config({
<center>[2] <b>Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University</b></center>
<br>
<p>
<center><h4>Oct 2, 2020</h4></center> <!-- date -->
<center><h4>Oct 4, 2020</h4></center> <!-- date -->
<br>
<p>
<!-- !split --><br><br><br><br><br><br><br><br><br><br>
@@ -195,7 +195,7 @@ MathJax.Hub.Config({
<ul>
<li> Thursday: Stochastic Gradient descent with examples and automatic differentiation and begin Neural Networks. <a href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h20/forelesningsvideoer/LectureOctober1.mp4?vrtx=view-as-webpage" target="_blank">Video of Lecture</a></li>
<li> Friday: Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model</li>
<li> Friday: Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model. <a href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h20/forelesningsvideoer/LectureOctober2.mp4?vrtx=view-as-webpage" target="_blank">Video of Lecture</a></li>
</ul>
Reading suggestions for both days: <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/Textbooks/TensorflowML.pdf" target="_blank">Aurelien Geron's chapter 10</a> and Hastie et al chapter 11.
doc/pub/week40/html/week40.html
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@@ -191,7 +191,7 @@ MathJax.Hub.Config({
<center>[2] <b>Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University</b></center>
<br>
<p>
<center><h4>Oct 2, 2020</h4></center> <!-- date -->
<center><h4>Oct 4, 2020</h4></center> <!-- date -->
<br>
<p>
<!-- !split --><br><br><br><br><br><br><br><br><br><br>
@@ -200,7 +200,7 @@ MathJax.Hub.Config({
<ul>
<li> Thursday: Stochastic Gradient descent with examples and automatic differentiation and begin Neural Networks. <a href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h20/forelesningsvideoer/LectureOctober1.mp4?vrtx=view-as-webpage" target="_blank">Video of Lecture</a></li>
<li> Friday: Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model</li>
<li> Friday: Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model. <a href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h20/forelesningsvideoer/LectureOctober2.mp4?vrtx=view-as-webpage" target="_blank">Video of Lecture</a></li>
</ul>
Reading suggestions for both days: <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/Textbooks/TensorflowML.pdf" target="_blank">Aurelien Geron's chapter 10</a> and Hastie et al chapter 11.
doc/pub/week40/ipynb/ipynb-week40-src.tar.gz
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doc/pub/week40/ipynb/week40.ipynb
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@@ -10,7 +10,7 @@
"<!-- 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: **Oct 2, 2020**\n",
"Date: **Oct 4, 2020**\n",
"\n",
"Copyright 1999-2020, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license\n",
"\n",
@@ -21,7 +21,7 @@
"\n",
"* Thursday: Stochastic Gradient descent with examples and automatic differentiation and begin Neural Networks. [Video of Lecture](https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h20/forelesningsvideoer/LectureOctober1.mp4?vrtx=view-as-webpage) \n",
"\n",
"* Friday: Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model\n",
"* Friday: Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model. [Video of Lecture](https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h20/forelesningsvideoer/LectureOctober2.mp4?vrtx=view-as-webpage) \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",
"For Stochastic Gradient Descent, we recommend chapter 4 of Geron's text. \n",
@@ -142,7 +142,9 @@
{
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"metadata": {},
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"import numpy as np \n",
@@ -204,7 +206,9 @@
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"metadata": {
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"source": [
"import numpy as np \n",
@@ -243,7 +247,9 @@
{
"cell_type": "code",
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"source": [
"%matplotlib inline\n",
@@ -798,7 +804,9 @@
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import autograd.numpy as np\n",
@@ -854,7 +862,9 @@
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import autograd.numpy as np\n",
@@ -890,7 +900,9 @@
{
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"metadata": {},
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"source": [
"import autograd.numpy as np\n",
@@ -941,7 +953,9 @@
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"metadata": {
"collapsed": false
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"outputs": [],
"source": [
"import autograd.numpy as np\n",
@@ -981,7 +995,9 @@
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import autograd.numpy as np\n",
@@ -1013,7 +1029,9 @@
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import autograd.numpy as np\n",
@@ -1072,7 +1090,9 @@
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import autograd.numpy as np\n",
@@ -1096,7 +1116,9 @@
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import autograd.numpy as np\n",
@@ -1143,7 +1165,9 @@
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import autograd.numpy as np\n",
@@ -1171,7 +1195,9 @@
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import autograd.numpy as np\n",
@@ -1199,7 +1225,9 @@
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import autograd.numpy as np\n",
@@ -1229,7 +1257,9 @@
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"a += b\n",
@@ -1822,7 +1852,9 @@
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"\"\"\"The sigmoid function (or the logistic curve) is a \n",
@@ -2530,25 +2562,7 @@
]
}
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