diff --git a/doc/pub/week39/html/week39-reveal.html b/doc/pub/week39/html/week39-reveal.html
index 31fd0418e..c5d92e266 100644
--- a/doc/pub/week39/html/week39-reveal.html
+++ b/doc/pub/week39/html/week39-reveal.html
@@ -3495,7 +3495,7 @@ delta_momentum = <span style="color: #B452CD">0.3</span>
       <div class="input_area">
         <div class="highlight" style="background: #eeeedd">
   <pre style="font-size: 80%; line-height: 125%;"><span style="color: #228B22"># Using Autograd to calculate gradients using SGD</span>
-<span style="color: #228B22"># OLS example</span>
+<span style="color: #228B22"># OLS example with AdaGrad</span>
 <span style="color: #8B008B; font-weight: bold">from</span> <span style="color: #008b45; text-decoration: underline">random</span> <span style="color: #8B008B; font-weight: bold">import</span> random, seed
 <span style="color: #8B008B; font-weight: bold">import</span> <span style="color: #008b45; text-decoration: underline">numpy</span> <span style="color: #8B008B; font-weight: bold">as</span> <span style="color: #008b45; text-decoration: underline">np</span>
 <span style="color: #8B008B; font-weight: bold">import</span> <span style="color: #008b45; text-decoration: underline">autograd.numpy</span> <span style="color: #8B008B; font-weight: bold">as</span> <span style="color: #008b45; text-decoration: underline">np</span>
@@ -3539,9 +3539,9 @@ M = <span style="color: #B452CD">5</span>   <span style="color: #228B22">#size o
 m = <span style="color: #658b00">int</span>(n/M) <span style="color: #228B22">#number of minibatches</span>
 theta = np.random.randn(<span style="color: #B452CD">2</span>,<span style="color: #B452CD">1</span>)
 
-
 <span style="color: #228B22"># Including AdaGrad</span>
 delta  = <span style="color: #B452CD">0.000001</span>
+r = [<span style="color: #B452CD">0.0</span> <span style="color: #8B008B; font-weight: bold">for</span> _ <span style="color: #8B008B">in</span> <span style="color: #658b00">range</span>(gradients.shape[<span style="color: #B452CD">0</span>])]
 <span style="color: #8B008B; font-weight: bold">for</span> epoch <span style="color: #8B008B">in</span> <span style="color: #658b00">range</span>(n_epochs):
     <span style="color: #8B008B; font-weight: bold">for</span> i <span style="color: #8B008B">in</span> <span style="color: #658b00">range</span>(m):
         random_index = M*np.random.randint(m)
@@ -3551,8 +3551,8 @@ delta  = <span style="color: #B452CD">0.000001</span>
         <span style="color: #228B22"># calculate squared gradient by Hadamard multiplication</span>
         r -= gradients*gradients
         <span style="color: #228B22"># compute update</span>
-        update = (<span style="color: #B452CD">1.0</span>/delta+np.sqrt(r))*gradients
-        theta = eta*update
+        update = <span style="color: #B452CD">1.0</span>/(delta+np.sqrt(r))*gradients
+        theta -= eta*update
 <span style="color: #658b00">print</span>(<span style="color: #CD5555">&quot;theta from own AdaGrad&quot;</span>)
 <span style="color: #658b00">print</span>(theta)
 </pre>
diff --git a/doc/pub/week39/html/week39-solarized.html b/doc/pub/week39/html/week39-solarized.html
index 76bc2d149..d6d819d95 100644
--- a/doc/pub/week39/html/week39-solarized.html
+++ b/doc/pub/week39/html/week39-solarized.html
@@ -3422,7 +3422,7 @@ delta_momentum = <span style="color: #B452CD">0.3</span>
       <div class="input_area">
         <div class="highlight" style="background: #eeeedd">
   <pre style="line-height: 125%;"><span style="color: #228B22"># Using Autograd to calculate gradients using SGD</span>
-<span style="color: #228B22"># OLS example</span>
+<span style="color: #228B22"># OLS example with AdaGrad</span>
 <span style="color: #8B008B; font-weight: bold">from</span> <span style="color: #008b45; text-decoration: underline">random</span> <span style="color: #8B008B; font-weight: bold">import</span> random, seed
 <span style="color: #8B008B; font-weight: bold">import</span> <span style="color: #008b45; text-decoration: underline">numpy</span> <span style="color: #8B008B; font-weight: bold">as</span> <span style="color: #008b45; text-decoration: underline">np</span>
 <span style="color: #8B008B; font-weight: bold">import</span> <span style="color: #008b45; text-decoration: underline">autograd.numpy</span> <span style="color: #8B008B; font-weight: bold">as</span> <span style="color: #008b45; text-decoration: underline">np</span>
@@ -3466,9 +3466,9 @@ M = <span style="color: #B452CD">5</span>   <span style="color: #228B22">#size o
 m = <span style="color: #658b00">int</span>(n/M) <span style="color: #228B22">#number of minibatches</span>
 theta = np.random.randn(<span style="color: #B452CD">2</span>,<span style="color: #B452CD">1</span>)
 
-
 <span style="color: #228B22"># Including AdaGrad</span>
 delta  = <span style="color: #B452CD">0.000001</span>
+r = [<span style="color: #B452CD">0.0</span> <span style="color: #8B008B; font-weight: bold">for</span> _ <span style="color: #8B008B">in</span> <span style="color: #658b00">range</span>(gradients.shape[<span style="color: #B452CD">0</span>])]
 <span style="color: #8B008B; font-weight: bold">for</span> epoch <span style="color: #8B008B">in</span> <span style="color: #658b00">range</span>(n_epochs):
     <span style="color: #8B008B; font-weight: bold">for</span> i <span style="color: #8B008B">in</span> <span style="color: #658b00">range</span>(m):
         random_index = M*np.random.randint(m)
@@ -3478,8 +3478,8 @@ delta  = <span style="color: #B452CD">0.000001</span>
         <span style="color: #228B22"># calculate squared gradient by Hadamard multiplication</span>
         r -= gradients*gradients
         <span style="color: #228B22"># compute update</span>
-        update = (<span style="color: #B452CD">1.0</span>/delta+np.sqrt(r))*gradients
-        theta = eta*update
+        update = <span style="color: #B452CD">1.0</span>/(delta+np.sqrt(r))*gradients
+        theta -= eta*update
 <span style="color: #658b00">print</span>(<span style="color: #CD5555">&quot;theta from own AdaGrad&quot;</span>)
 <span style="color: #658b00">print</span>(theta)
 </pre>
diff --git a/doc/pub/week39/html/week39.html b/doc/pub/week39/html/week39.html
index 953335216..2d7932742 100644
--- a/doc/pub/week39/html/week39.html
+++ b/doc/pub/week39/html/week39.html
@@ -3499,7 +3499,7 @@ delta_momentum <span style="color: #666666">=</span> <span style="color: #666666
       <div class="input_area">
         <div class="highlight" style="background: #f8f8f8">
   <pre style="line-height: 125%;"><span style="color: #408080; font-style: italic"># Using Autograd to calculate gradients using SGD</span>
-<span style="color: #408080; font-style: italic"># OLS example</span>
+<span style="color: #408080; font-style: italic"># OLS example with AdaGrad</span>
 <span style="color: #008000; font-weight: bold">from</span> <span style="color: #0000FF; font-weight: bold">random</span> <span style="color: #008000; font-weight: bold">import</span> random, seed
 <span style="color: #008000; font-weight: bold">import</span> <span style="color: #0000FF; font-weight: bold">numpy</span> <span style="color: #008000; font-weight: bold">as</span> <span style="color: #0000FF; font-weight: bold">np</span>
 <span style="color: #008000; font-weight: bold">import</span> <span style="color: #0000FF; font-weight: bold">autograd.numpy</span> <span style="color: #008000; font-weight: bold">as</span> <span style="color: #0000FF; font-weight: bold">np</span>
@@ -3543,9 +3543,9 @@ M <span style="color: #666666">=</span> <span style="color: #666666">5</span>
 m <span style="color: #666666">=</span> <span style="color: #008000">int</span>(n<span style="color: #666666">/</span>M) <span style="color: #408080; font-style: italic">#number of minibatches</span>
 theta <span style="color: #666666">=</span> np<span style="color: #666666">.</span>random<span style="color: #666666">.</span>randn(<span style="color: #666666">2</span>,<span style="color: #666666">1</span>)
 
-
 <span style="color: #408080; font-style: italic"># Including AdaGrad</span>
 delta  <span style="color: #666666">=</span> <span style="color: #666666">0.000001</span>
+r <span style="color: #666666">=</span> [<span style="color: #666666">0.0</span> <span style="color: #008000; font-weight: bold">for</span> _ <span style="color: #AA22FF; font-weight: bold">in</span> <span style="color: #008000">range</span>(gradients<span style="color: #666666">.</span>shape[<span style="color: #666666">0</span>])]
 <span style="color: #008000; font-weight: bold">for</span> epoch <span style="color: #AA22FF; font-weight: bold">in</span> <span style="color: #008000">range</span>(n_epochs):
     <span style="color: #008000; font-weight: bold">for</span> i <span style="color: #AA22FF; font-weight: bold">in</span> <span style="color: #008000">range</span>(m):
         random_index <span style="color: #666666">=</span> M<span style="color: #666666">*</span>np<span style="color: #666666">.</span>random<span style="color: #666666">.</span>randint(m)
@@ -3555,8 +3555,8 @@ delta  <span style="color: #666666">=</span> <span style="color: #666666">0.0000
         <span style="color: #408080; font-style: italic"># calculate squared gradient by Hadamard multiplication</span>
         r <span style="color: #666666">-=</span> gradients<span style="color: #666666">*</span>gradients
         <span style="color: #408080; font-style: italic"># compute update</span>
-        update <span style="color: #666666">=</span> (<span style="color: #666666">1.0/</span>delta<span style="color: #666666">+</span>np<span style="color: #666666">.</span>sqrt(r))<span style="color: #666666">*</span>gradients
-        theta <span style="color: #666666">=</span> eta<span style="color: #666666">*</span>update
+        update <span style="color: #666666">=</span> <span style="color: #666666">1.0/</span>(delta<span style="color: #666666">+</span>np<span style="color: #666666">.</span>sqrt(r))<span style="color: #666666">*</span>gradients
+        theta <span style="color: #666666">-=</span> eta<span style="color: #666666">*</span>update
 <span style="color: #008000">print</span>(<span style="color: #BA2121">&quot;theta from own AdaGrad&quot;</span>)
 <span style="color: #008000">print</span>(theta)
 </pre>
diff --git a/doc/pub/week39/ipynb/ipynb-week39-src.tar.gz b/doc/pub/week39/ipynb/ipynb-week39-src.tar.gz
index 9b9d1c2cb..a6ec70f87 100644
Binary files a/doc/pub/week39/ipynb/ipynb-week39-src.tar.gz and b/doc/pub/week39/ipynb/ipynb-week39-src.tar.gz differ
diff --git a/doc/pub/week39/ipynb/week39.ipynb b/doc/pub/week39/ipynb/week39.ipynb
index 1e8f64dce..0503b55c1 100644
--- a/doc/pub/week39/ipynb/week39.ipynb
+++ b/doc/pub/week39/ipynb/week39.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "3090dab9",
+   "id": "70c42524",
    "metadata": {
     "editable": true
    },
@@ -14,7 +14,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ab0dea94",
+   "id": "cffad5f6",
    "metadata": {
     "editable": true
    },
@@ -29,7 +29,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9db200b9",
+   "id": "34c8fbcd",
    "metadata": {
     "editable": true
    },
@@ -55,7 +55,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "daa1efbf",
+   "id": "9e3863c0",
    "metadata": {
     "editable": true
    },
@@ -76,7 +76,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d67302c7",
+   "id": "aac1849d",
    "metadata": {
     "editable": true
    },
@@ -93,7 +93,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6cffc694",
+   "id": "eda84591",
    "metadata": {
     "editable": true
    },
@@ -108,7 +108,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7c0e4b41",
+   "id": "e5e6a3fc",
    "metadata": {
     "editable": true
    },
@@ -118,7 +118,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a4d042c9",
+   "id": "f5a2093d",
    "metadata": {
     "editable": true
    },
@@ -134,7 +134,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a2e6e6ca",
+   "id": "ababb255",
    "metadata": {
     "editable": true
    },
@@ -146,7 +146,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "44ba6d7f",
+   "id": "81ee053a",
    "metadata": {
     "editable": true
    },
@@ -157,7 +157,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f83dfe9e",
+   "id": "22359c61",
    "metadata": {
     "editable": true
    },
@@ -169,7 +169,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "36ae9e1f",
+   "id": "f41b1042",
    "metadata": {
     "editable": true
    },
@@ -179,7 +179,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f68dff87",
+   "id": "e7ff9f7e",
    "metadata": {
     "editable": true
    },
@@ -193,7 +193,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "1c04ada4",
+   "id": "488f1674",
    "metadata": {
     "editable": true
    },
@@ -205,7 +205,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "57d59ede",
+   "id": "fc58bce3",
    "metadata": {
     "editable": true
    },
@@ -215,7 +215,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6731c775",
+   "id": "9063bdf3",
    "metadata": {
     "editable": true
    },
@@ -227,7 +227,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "344395d0",
+   "id": "b60c1a1e",
    "metadata": {
     "editable": true
    },
@@ -239,7 +239,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "030a7dd9",
+   "id": "1836b157",
    "metadata": {
     "editable": true
    },
@@ -259,7 +259,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f714706e",
+   "id": "e1ecf421",
    "metadata": {
     "editable": true
    },
@@ -275,7 +275,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "bc0a90df",
+   "id": "d1696b80",
    "metadata": {
     "editable": true
    },
@@ -291,7 +291,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2ced70dc",
+   "id": "a9018f84",
    "metadata": {
     "editable": true
    },
@@ -302,7 +302,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f69cd4d8",
+   "id": "d8f2841f",
    "metadata": {
     "editable": true
    },
@@ -314,7 +314,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9478068d",
+   "id": "9623e5a1",
    "metadata": {
     "editable": true
    },
@@ -324,7 +324,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "66e95761",
+   "id": "624339a9",
    "metadata": {
     "editable": true
    },
@@ -336,7 +336,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3b1f9fb4",
+   "id": "642946f7",
    "metadata": {
     "editable": true
    },
@@ -346,7 +346,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "26695601",
+   "id": "6c05a90c",
    "metadata": {
     "editable": true
    },
@@ -358,7 +358,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "1951019b",
+   "id": "edcd1d95",
    "metadata": {
     "editable": true
    },
@@ -380,7 +380,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b38f86e5",
+   "id": "2928dbd1",
    "metadata": {
     "editable": true
    },
@@ -393,7 +393,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "81a4e8bd",
+   "id": "14edc1f1",
    "metadata": {
     "editable": true
    },
@@ -406,7 +406,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "12f207a8",
+   "id": "c6fcded8",
    "metadata": {
     "editable": true
    },
@@ -416,7 +416,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "440c1a73",
+   "id": "5d46ef00",
    "metadata": {
     "editable": true
    },
@@ -434,7 +434,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9e301758",
+   "id": "29230b7d",
    "metadata": {
     "editable": true
    },
@@ -444,7 +444,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "714caf32",
+   "id": "4050e8df",
    "metadata": {
     "editable": true
    },
@@ -459,7 +459,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "79945812",
+   "id": "b9acd139",
    "metadata": {
     "editable": true
    },
@@ -469,7 +469,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "821bfe43",
+   "id": "378b9253",
    "metadata": {
     "editable": true
    },
@@ -483,7 +483,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7a329d62",
+   "id": "0f5c3c0d",
    "metadata": {
     "editable": true
    },
@@ -493,7 +493,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a759ca7a",
+   "id": "bb12d0e0",
    "metadata": {
     "editable": true
    },
@@ -507,7 +507,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "37bd514e",
+   "id": "93274086",
    "metadata": {
     "editable": true
    },
@@ -522,7 +522,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "aa97f992",
+   "id": "122ee26a",
    "metadata": {
     "editable": true
    },
@@ -539,7 +539,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "67fa21b3",
+   "id": "4235ab9d",
    "metadata": {
     "editable": true
    },
@@ -551,7 +551,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f8f33cfa",
+   "id": "4fc1a870",
    "metadata": {
     "editable": true
    },
@@ -565,7 +565,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "12fcbcb4",
+   "id": "57d01841",
    "metadata": {
     "editable": true
    },
@@ -580,7 +580,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "247f240a",
+   "id": "1d84085f",
    "metadata": {
     "editable": true
    },
@@ -592,7 +592,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a7f4feb0",
+   "id": "a2a841e7",
    "metadata": {
     "editable": true
    },
@@ -603,7 +603,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "581dc6c7",
+   "id": "cfe42a8d",
    "metadata": {
     "editable": true
    },
@@ -631,7 +631,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "115cc2f5",
+   "id": "37e43c57",
    "metadata": {
     "editable": true
    },
@@ -653,7 +653,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "981820fd",
+   "id": "d73f9ec1",
    "metadata": {
     "editable": true
    },
@@ -675,7 +675,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "71769268",
+   "id": "9ef05d17",
    "metadata": {
     "editable": true
    },
@@ -687,7 +687,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7236d516",
+   "id": "84ad8b8f",
    "metadata": {
     "editable": true
    },
@@ -724,7 +724,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "1be5600b",
+   "id": "b73096ec",
    "metadata": {
     "editable": true
    },
@@ -752,7 +752,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "bc9479dd",
+   "id": "01363dd6",
    "metadata": {
     "editable": true
    },
@@ -782,7 +782,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b287dc6b",
+   "id": "3035712a",
    "metadata": {
     "editable": true
    },
@@ -802,7 +802,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f3b051c9",
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@@ -814,7 +814,7 @@
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@@ -824,7 +824,7 @@
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@@ -836,7 +836,7 @@
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@@ -848,7 +848,7 @@
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@@ -860,7 +860,7 @@
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@@ -872,7 +872,7 @@
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@@ -883,7 +883,7 @@
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@@ -896,7 +896,7 @@
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@@ -908,7 +908,7 @@
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@@ -918,7 +918,7 @@
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@@ -930,7 +930,7 @@
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@@ -940,7 +940,7 @@
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@@ -951,7 +951,7 @@
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@@ -963,7 +963,7 @@
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@@ -975,7 +975,7 @@
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@@ -987,7 +987,7 @@
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@@ -998,7 +998,7 @@
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@@ -1009,7 +1009,7 @@
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@@ -1021,7 +1021,7 @@
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@@ -1031,7 +1031,7 @@
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@@ -1043,7 +1043,7 @@
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@@ -1053,7 +1053,7 @@
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@@ -1065,7 +1065,7 @@
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@@ -1075,7 +1075,7 @@
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@@ -1087,7 +1087,7 @@
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@@ -1097,7 +1097,7 @@
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@@ -1109,7 +1109,7 @@
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@@ -1120,7 +1120,7 @@
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@@ -1153,7 +1153,7 @@
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@@ -1164,7 +1164,7 @@
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@@ -1178,7 +1178,7 @@
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@@ -1189,7 +1189,7 @@
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@@ -1202,7 +1202,7 @@
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@@ -1213,7 +1213,7 @@
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@@ -1231,7 +1231,7 @@
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@@ -1242,7 +1242,7 @@
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@@ -1257,7 +1257,7 @@
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@@ -1267,7 +1267,7 @@
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@@ -1281,7 +1281,7 @@
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@@ -1293,7 +1293,7 @@
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@@ -1304,7 +1304,7 @@
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@@ -1316,7 +1316,7 @@
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@@ -1327,7 +1327,7 @@
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@@ -1338,7 +1338,7 @@
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@@ -1350,7 +1350,7 @@
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@@ -1360,7 +1360,7 @@
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@@ -1372,7 +1372,7 @@
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@@ -1384,7 +1384,7 @@
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@@ -1396,7 +1396,7 @@
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@@ -1408,7 +1408,7 @@
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@@ -1419,7 +1419,7 @@
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@@ -1431,7 +1431,7 @@
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@@ -1441,7 +1441,7 @@
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@@ -1453,7 +1453,7 @@
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@@ -1463,7 +1463,7 @@
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@@ -1475,7 +1475,7 @@
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@@ -1495,7 +1495,7 @@
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@@ -1507,7 +1507,7 @@
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@@ -1517,7 +1517,7 @@
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@@ -1529,7 +1529,7 @@
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@@ -1539,7 +1539,7 @@
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@@ -1550,7 +1550,7 @@
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@@ -1562,7 +1562,7 @@
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@@ -1574,7 +1574,7 @@
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@@ -1586,7 +1586,7 @@
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@@ -1599,7 +1599,7 @@
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@@ -1610,7 +1610,7 @@
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@@ -1622,7 +1622,7 @@
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@@ -1638,7 +1638,7 @@
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@@ -1650,7 +1650,7 @@
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@@ -1661,7 +1661,7 @@
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@@ -1673,7 +1673,7 @@
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@@ -1683,7 +1683,7 @@
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@@ -1695,7 +1695,7 @@
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@@ -1705,7 +1705,7 @@
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@@ -1717,7 +1717,7 @@
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@@ -1727,7 +1727,7 @@
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@@ -1739,7 +1739,7 @@
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@@ -1763,7 +1763,7 @@
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@@ -1776,7 +1776,7 @@
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@@ -1787,7 +1787,7 @@
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@@ -1799,7 +1799,7 @@
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@@ -1809,7 +1809,7 @@
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@@ -1821,7 +1821,7 @@
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@@ -1835,7 +1835,7 @@
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@@ -1851,7 +1851,7 @@
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@@ -1861,7 +1861,7 @@
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@@ -1873,7 +1873,7 @@
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@@ -1883,7 +1883,7 @@
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@@ -1895,7 +1895,7 @@
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@@ -1909,7 +1909,7 @@
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@@ -1919,7 +1919,7 @@
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@@ -1930,7 +1930,7 @@
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@@ -1945,7 +1945,7 @@
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@@ -1955,7 +1955,7 @@
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@@ -1967,7 +1967,7 @@
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@@ -1979,7 +1979,7 @@
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@@ -1994,7 +1994,7 @@
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@@ -2007,7 +2007,7 @@
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@@ -2064,7 +2064,7 @@
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@@ -2075,7 +2075,7 @@
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@@ -2102,7 +2102,7 @@
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@@ -2114,7 +2114,7 @@
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@@ -2126,7 +2126,7 @@
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@@ -2136,7 +2136,7 @@
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@@ -2150,7 +2150,7 @@
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@@ -2160,7 +2160,7 @@
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@@ -2172,7 +2172,7 @@
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@@ -2183,7 +2183,7 @@
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@@ -2198,7 +2198,7 @@
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@@ -2212,7 +2212,7 @@
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@@ -2223,7 +2223,7 @@
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@@ -2284,7 +2284,7 @@
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@@ -2306,7 +2306,7 @@
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@@ -2319,7 +2319,7 @@
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@@ -2385,7 +2385,7 @@
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@@ -2396,7 +2396,7 @@
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@@ -2470,7 +2470,7 @@
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@@ -2482,7 +2482,7 @@
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@@ -2503,7 +2503,7 @@
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@@ -2535,7 +2535,7 @@
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@@ -2552,7 +2552,7 @@
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@@ -2565,7 +2565,7 @@
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@@ -2578,7 +2578,7 @@
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@@ -2591,7 +2591,7 @@
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@@ -2605,7 +2605,7 @@
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@@ -2627,7 +2627,7 @@
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@@ -2642,7 +2642,7 @@
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@@ -2654,7 +2654,7 @@
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@@ -2667,7 +2667,7 @@
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@@ -2681,7 +2681,7 @@
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@@ -2692,7 +2692,7 @@
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@@ -2717,7 +2717,7 @@
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@@ -2733,7 +2733,7 @@
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@@ -2754,7 +2754,7 @@
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@@ -2774,7 +2774,7 @@
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@@ -2793,7 +2793,7 @@
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@@ -2828,7 +2828,7 @@
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@@ -2841,7 +2841,7 @@
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@@ -2918,7 +2918,7 @@
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@@ -2933,7 +2933,7 @@
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@@ -2948,7 +2948,7 @@
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@@ -2960,7 +2960,7 @@
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@@ -2978,7 +2978,7 @@
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@@ -2997,7 +2997,7 @@
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@@ -3009,7 +3009,7 @@
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@@ -3019,7 +3019,7 @@
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@@ -3035,7 +3035,7 @@
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@@ -3047,7 +3047,7 @@
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@@ -3057,7 +3057,7 @@
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@@ -3069,7 +3069,7 @@
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@@ -3079,7 +3079,7 @@
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@@ -3091,7 +3091,7 @@
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@@ -3107,7 +3107,7 @@
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@@ -3119,7 +3119,7 @@
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@@ -3152,7 +3152,7 @@
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@@ -3164,7 +3164,7 @@
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@@ -3182,7 +3182,7 @@
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@@ -3192,7 +3192,7 @@
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@@ -3223,7 +3223,7 @@
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@@ -3238,7 +3238,7 @@
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@@ -3256,7 +3256,7 @@
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@@ -3268,7 +3268,7 @@
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@@ -3280,7 +3280,7 @@
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@@ -3298,7 +3298,7 @@
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@@ -3321,7 +3321,7 @@
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@@ -3339,7 +3339,7 @@
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@@ -3351,7 +3351,7 @@
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@@ -3363,7 +3363,7 @@
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@@ -3375,7 +3375,7 @@
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@@ -3387,7 +3387,7 @@
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@@ -3399,7 +3399,7 @@
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@@ -3416,7 +3416,7 @@
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@@ -3435,7 +3435,7 @@
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@@ -3447,7 +3447,7 @@
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@@ -3467,7 +3467,7 @@
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@@ -3505,7 +3505,7 @@
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@@ -3517,7 +3517,7 @@
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@@ -3527,7 +3527,7 @@
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@@ -3539,7 +3539,7 @@
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@@ -3550,7 +3550,7 @@
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@@ -3595,7 +3595,7 @@
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@@ -3612,7 +3612,7 @@
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@@ -3640,7 +3640,7 @@
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@@ -3655,7 +3655,7 @@
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@@ -3699,7 +3699,7 @@
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@@ -3709,7 +3709,7 @@
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@@ -3720,7 +3720,7 @@
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@@ -3748,7 +3748,7 @@
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@@ -3763,7 +3763,7 @@
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@@ -3774,7 +3774,7 @@
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@@ -3802,7 +3802,7 @@
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@@ -3813,7 +3813,7 @@
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@@ -3838,7 +3838,7 @@
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@@ -3849,7 +3849,7 @@
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@@ -3885,7 +3885,7 @@
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@@ -3905,7 +3905,7 @@
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@@ -3916,7 +3916,7 @@
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@@ -3954,7 +3954,7 @@
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@@ -3964,7 +3964,7 @@
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@@ -3978,7 +3978,7 @@
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+   "id": "7e1c00c8",
    "metadata": {
     "collapsed": false,
     "editable": true
@@ -4000,7 +4000,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4457eba3",
+   "id": "91b32000",
    "metadata": {
     "editable": true
    },
@@ -4010,7 +4010,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d6303490",
+   "id": "5bb6505b",
    "metadata": {
     "editable": true
    },
@@ -4021,7 +4021,7 @@
   {
    "cell_type": "code",
    "execution_count": 25,
-   "id": "7dd580f0",
+   "id": "b698d800",
    "metadata": {
     "collapsed": false,
     "editable": true
@@ -4043,7 +4043,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "27629408",
+   "id": "7daefc20",
    "metadata": {
     "editable": true
    },
@@ -4056,7 +4056,7 @@
   {
    "cell_type": "code",
    "execution_count": 26,
-   "id": "30c2ae6c",
+   "id": "f4db3939",
    "metadata": {
     "collapsed": false,
     "editable": true
@@ -4081,7 +4081,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "106e6e20",
+   "id": "63911856",
    "metadata": {
     "editable": true
    },
@@ -4093,7 +4093,7 @@
   {
    "cell_type": "code",
    "execution_count": 27,
-   "id": "4aa28359",
+   "id": "fc661b03",
    "metadata": {
     "collapsed": false,
     "editable": true
@@ -4108,7 +4108,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "0b41db61",
+   "id": "a873728b",
    "metadata": {
     "editable": true
    },
@@ -4123,7 +4123,7 @@
   {
    "cell_type": "code",
    "execution_count": 28,
-   "id": "0a3e77af",
+   "id": "68ec2659",
    "metadata": {
     "collapsed": false,
     "editable": true
@@ -4183,7 +4183,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d66b1248",
+   "id": "7a2e9992",
    "metadata": {
     "editable": true
    },
@@ -4194,7 +4194,7 @@
   {
    "cell_type": "code",
    "execution_count": 29,
-   "id": "62fd741e",
+   "id": "b03e6d68",
    "metadata": {
     "collapsed": false,
     "editable": true
@@ -4258,7 +4258,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ea73ead4",
+   "id": "d518ed04",
    "metadata": {
     "editable": true
    },
@@ -4269,7 +4269,7 @@
   {
    "cell_type": "code",
    "execution_count": 30,
-   "id": "85769e6a",
+   "id": "4f365ef3",
    "metadata": {
     "collapsed": false,
     "editable": true
@@ -4318,7 +4318,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c72ceec5",
+   "id": "bb7a2b23",
    "metadata": {
     "editable": true
    },
@@ -4330,7 +4330,7 @@
   {
    "cell_type": "code",
    "execution_count": 31,
-   "id": "03605486",
+   "id": "7be1bad2",
    "metadata": {
     "collapsed": false,
     "editable": true
@@ -4414,7 +4414,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "44a2e49e",
+   "id": "998c490d",
    "metadata": {
     "editable": true
    },
@@ -4425,7 +4425,7 @@
   {
    "cell_type": "code",
    "execution_count": 32,
-   "id": "605503fb",
+   "id": "8c8323d7",
    "metadata": {
     "collapsed": false,
     "editable": true
@@ -4503,7 +4503,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "423148e4",
+   "id": "e8e20118",
    "metadata": {
     "editable": true
    },
@@ -4514,7 +4514,7 @@
   {
    "cell_type": "code",
    "execution_count": 33,
-   "id": "b025c34c",
+   "id": "38b88401",
    "metadata": {
     "collapsed": false,
     "editable": true
@@ -4522,7 +4522,7 @@
    "outputs": [],
    "source": [
     "# Using Autograd to calculate gradients using SGD\n",
-    "# OLS example\n",
+    "# OLS example with AdaGrad\n",
     "from random import random, seed\n",
     "import numpy as np\n",
     "import autograd.numpy as np\n",
@@ -4566,9 +4566,9 @@
     "m = int(n/M) #number of minibatches\n",
     "theta = np.random.randn(2,1)\n",
     "\n",
-    "\n",
     "# Including AdaGrad\n",
     "delta  = 0.000001\n",
+    "r = [0.0 for _ in range(gradients.shape[0])]\n",
     "for epoch in range(n_epochs):\n",
     "    for i in range(m):\n",
     "        random_index = M*np.random.randint(m)\n",
@@ -4578,15 +4578,15 @@
     "        # calculate squared gradient by Hadamard multiplication\n",
     "        r -= gradients*gradients\n",
     "        # compute update\n",
-    "        update = (1.0/delta+np.sqrt(r))*gradients\n",
-    "        theta = eta*update\n",
+    "        update = 1.0/(delta+np.sqrt(r))*gradients\n",
+    "        theta -= eta*update\n",
     "print(\"theta from own AdaGrad\")\n",
     "print(theta)"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "a1aebdad",
+   "id": "0989e18a",
    "metadata": {
     "editable": true
    },
@@ -4597,7 +4597,7 @@
   {
    "cell_type": "code",
    "execution_count": 34,
-   "id": "1091d4ae",
+   "id": "c6622d90",
    "metadata": {
     "collapsed": false,
     "editable": true
@@ -4641,7 +4641,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f08388a7",
+   "id": "442a319f",
    "metadata": {
     "editable": true
    },
@@ -4660,7 +4660,7 @@
   {
    "cell_type": "code",
    "execution_count": 35,
-   "id": "131b959a",
+   "id": "8c6259ef",
    "metadata": {
     "collapsed": false,
     "editable": true
@@ -4680,7 +4680,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "426864d6",
+   "id": "4495aa58",
    "metadata": {
     "editable": true
    },
diff --git a/doc/src/week39/adagrad.py b/doc/src/week39/adagrad.py
index 783124245..dbee993c6 100644
--- a/doc/src/week39/adagrad.py
+++ b/doc/src/week39/adagrad.py
@@ -43,9 +43,9 @@ M = 5   #size of each minibatch
 m = int(n/M) #number of minibatches
 theta = np.random.randn(2,1)
 
-
 # Including AdaGrad
 delta  = 0.000001
+r = [0.0 for _ in range(gradients.shape[0])]
 for epoch in range(n_epochs):
     for i in range(m):
         random_index = M*np.random.randint(m)
@@ -55,8 +55,8 @@ for epoch in range(n_epochs):
         # calculate squared gradient by Hadamard multiplication
         r -= gradients*gradients
         # compute update
-        update = (1.0/delta+np.sqrt(r))*gradients
-        theta = eta*update
+        update = 1.0/(delta+np.sqrt(r))*gradients
+        theta -= eta*update
 print("theta from own AdaGrad")
 print(theta)
 
diff --git a/doc/src/week39/week39.do.txt b/doc/src/week39/week39.do.txt
index 26a1b4311..33d3d3cf3 100644
--- a/doc/src/week39/week39.do.txt
+++ b/doc/src/week39/week39.do.txt
@@ -2435,7 +2435,7 @@ print(theta)
 ===== Same problem but now with AdaGrad =====
 !bc pycod
 # Using Autograd to calculate gradients using SGD
-# OLS example
+# OLS example with AdaGrad
 from random import random, seed
 import numpy as np
 import autograd.numpy as np
@@ -2479,9 +2479,9 @@ M = 5   #size of each minibatch
 m = int(n/M) #number of minibatches
 theta = np.random.randn(2,1)
 
-
 # Including AdaGrad
 delta  = 0.000001
+r = [0.0 for _ in range(gradients.shape[0])]
 for epoch in range(n_epochs):
     for i in range(m):
         random_index = M*np.random.randint(m)
@@ -2491,11 +2491,10 @@ for epoch in range(n_epochs):
         # calculate squared gradient by Hadamard multiplication
         r -= gradients*gradients
         # compute update
-        update = (1.0/delta+np.sqrt(r))*gradients
-        theta = eta*update
+        update = 1.0/(delta+np.sqrt(r))*gradients
+        theta -= eta*update
 print("theta from own AdaGrad")
 print(theta)
-
 !ec