From afd3c43fc6bad042761c3d5b963819a554f2dce9 Mon Sep 17 00:00:00 2001
From: Morten Hjorth-Jensen <morten.hjorth-jensen@fys.uio.no>
Date: Mon, 21 Aug 2023 09:03:12 +0200
Subject: [PATCH] update

---
 doc/pub/week34/html/._week34-bs018.html      |   2 +-
 doc/pub/week34/html/week34-reveal.html       |   2 +-
 doc/pub/week34/html/week34-solarized.html    |   2 +-
 doc/pub/week34/html/week34.html              |   2 +-
 doc/pub/week34/ipynb/ipynb-week34-src.tar.gz | Bin 103516 -> 103516 bytes
 doc/pub/week34/ipynb/week34.ipynb            | 604 +++++++++----------
 doc/src/week34/week34.do.txt                 |   2 +-
 7 files changed, 307 insertions(+), 307 deletions(-)

diff --git a/doc/pub/week34/html/._week34-bs018.html b/doc/pub/week34/html/._week34-bs018.html
index 0f7f2b313..7ad83bb86 100644
--- a/doc/pub/week34/html/._week34-bs018.html
+++ b/doc/pub/week34/html/._week34-bs018.html
@@ -384,7 +384,7 @@ specifically, after this course you will
 <li> Learn about about decision trees, random forests, bagging and boosting methods;</li>
 <li> Learn about support vector machines and kernel transformations;</li>
 <li> Reduction of data sets, from PCA to clustering;</li>
-<li> Autoencoders and Reinforcement Learning;</li>
+<li> Generative models</li>
 <li> Work on numerical projects to illustrate the theory. The projects play a central role and you are expected to know modern programming languages like Python or C++ and/or Fortran (Fortran2003 or later) or Julia or other.</li>
 </ul>
 </div>
diff --git a/doc/pub/week34/html/week34-reveal.html b/doc/pub/week34/html/week34-reveal.html
index 7da26d655..d2ce03a1d 100644
--- a/doc/pub/week34/html/week34-reveal.html
+++ b/doc/pub/week34/html/week34-reveal.html
@@ -513,7 +513,7 @@ specifically, after this course you will
 <p><li> Learn about about decision trees, random forests, bagging and boosting methods;</li>
 <p><li> Learn about support vector machines and kernel transformations;</li>
 <p><li> Reduction of data sets, from PCA to clustering;</li>
-<p><li> Autoencoders and Reinforcement Learning;</li>
+<p><li> Generative models</li>
 <p><li> Work on numerical projects to illustrate the theory. The projects play a central role and you are expected to know modern programming languages like Python or C++ and/or Fortran (Fortran2003 or later) or Julia or other.</li>
 </ul>
 </div>
diff --git a/doc/pub/week34/html/week34-solarized.html b/doc/pub/week34/html/week34-solarized.html
index c7aea082f..c63d3e7e9 100644
--- a/doc/pub/week34/html/week34-solarized.html
+++ b/doc/pub/week34/html/week34-solarized.html
@@ -566,7 +566,7 @@ specifically, after this course you will
 <li> Learn about about decision trees, random forests, bagging and boosting methods;</li>
 <li> Learn about support vector machines and kernel transformations;</li>
 <li> Reduction of data sets, from PCA to clustering;</li>
-<li> Autoencoders and Reinforcement Learning;</li>
+<li> Generative models</li>
 <li> Work on numerical projects to illustrate the theory. The projects play a central role and you are expected to know modern programming languages like Python or C++ and/or Fortran (Fortran2003 or later) or Julia or other.</li>
 </ul>
 </div>
diff --git a/doc/pub/week34/html/week34.html b/doc/pub/week34/html/week34.html
index 359429ca8..a084049f9 100644
--- a/doc/pub/week34/html/week34.html
+++ b/doc/pub/week34/html/week34.html
@@ -643,7 +643,7 @@ specifically, after this course you will
 <li> Learn about about decision trees, random forests, bagging and boosting methods;</li>
 <li> Learn about support vector machines and kernel transformations;</li>
 <li> Reduction of data sets, from PCA to clustering;</li>
-<li> Autoencoders and Reinforcement Learning;</li>
+<li> Generative models</li>
 <li> Work on numerical projects to illustrate the theory. The projects play a central role and you are expected to know modern programming languages like Python or C++ and/or Fortran (Fortran2003 or later) or Julia or other.</li>
 </ul>
 </div>
diff --git a/doc/pub/week34/ipynb/ipynb-week34-src.tar.gz b/doc/pub/week34/ipynb/ipynb-week34-src.tar.gz
index 012bf5605af00e92ab573584cee094b982764a52..1b9c8df0235799cb4d5cea781fc0379c39975bef 100644
GIT binary patch
delta 20
bcmcb!g6+-<Ha7Wg4hB`8Mz*bNjA2s%N}UEP

delta 20
bcmcb!g6+-<Ha7Wg4hD1XMz*bNjA2s%OE(5Q

diff --git a/doc/pub/week34/ipynb/week34.ipynb b/doc/pub/week34/ipynb/week34.ipynb
index 6051ac5d1..ffdf1d3dd 100644
--- a/doc/pub/week34/ipynb/week34.ipynb
+++ b/doc/pub/week34/ipynb/week34.ipynb
@@ -2,7 +2,7 @@
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+   "id": "c92946b1",
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@@ -14,7 +14,7 @@
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@@ -27,7 +27,7 @@
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@@ -51,7 +51,7 @@
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@@ -67,7 +67,7 @@
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@@ -91,7 +91,7 @@
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@@ -105,7 +105,7 @@
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@@ -127,7 +127,7 @@
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@@ -157,7 +157,7 @@
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+   "id": "62d2446b",
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@@ -175,7 +175,7 @@
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+   "id": "5d01da3f",
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@@ -189,7 +189,7 @@
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+   "id": "fdfee07f",
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@@ -207,7 +207,7 @@
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+   "id": "853104fe",
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@@ -219,7 +219,7 @@
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+   "id": "365738a4",
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@@ -239,7 +239,7 @@
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+   "id": "9a5404b2",
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@@ -257,7 +257,7 @@
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+   "id": "e13ecff8",
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@@ -282,7 +282,7 @@
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-   "id": "e65d1e50",
+   "id": "ac16b647",
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@@ -318,7 +318,7 @@
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+   "id": "98ae506a",
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@@ -334,7 +334,7 @@
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+   "id": "52da3685",
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@@ -356,7 +356,7 @@
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+   "id": "d6a03858",
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@@ -374,7 +374,7 @@
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+   "id": "bb6ed9d3",
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@@ -411,14 +411,14 @@
     "\n",
     "* Reduction of data sets, from PCA to clustering;\n",
     "\n",
-    "* Autoencoders and Reinforcement Learning;\n",
+    "* Generative models\n",
     "\n",
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    ]
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-   "id": "f78315f7",
+   "id": "9fdc6fb1",
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@@ -461,7 +461,7 @@
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@@ -481,7 +481,7 @@
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@@ -554,7 +554,7 @@
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@@ -583,7 +583,7 @@
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@@ -601,7 +601,7 @@
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@@ -613,7 +613,7 @@
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@@ -648,7 +648,7 @@
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@@ -678,7 +678,7 @@
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@@ -709,7 +709,7 @@
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@@ -748,7 +748,7 @@
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@@ -781,7 +781,7 @@
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@@ -816,7 +816,7 @@
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@@ -840,7 +840,7 @@
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@@ -867,7 +867,7 @@
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@@ -877,7 +877,7 @@
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@@ -889,7 +889,7 @@
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@@ -910,7 +910,7 @@
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@@ -922,7 +922,7 @@
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@@ -934,7 +934,7 @@
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@@ -945,7 +945,7 @@
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@@ -959,7 +959,7 @@
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@@ -971,7 +971,7 @@
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@@ -985,7 +985,7 @@
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@@ -997,7 +997,7 @@
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@@ -1011,7 +1011,7 @@
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@@ -1028,7 +1028,7 @@
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@@ -1045,7 +1045,7 @@
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@@ -1057,7 +1057,7 @@
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@@ -1071,7 +1071,7 @@
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@@ -1082,7 +1082,7 @@
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@@ -1096,7 +1096,7 @@
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@@ -1107,7 +1107,7 @@
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@@ -1121,7 +1121,7 @@
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@@ -1136,7 +1136,7 @@
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@@ -1150,7 +1150,7 @@
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@@ -1161,7 +1161,7 @@
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@@ -1176,7 +1176,7 @@
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@@ -1187,7 +1187,7 @@
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@@ -1202,7 +1202,7 @@
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@@ -1240,7 +1240,7 @@
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@@ -1358,7 +1358,7 @@
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@@ -1450,7 +1450,7 @@
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@@ -1508,7 +1508,7 @@
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@@ -1520,7 +1520,7 @@
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@@ -1531,7 +1531,7 @@
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@@ -1549,7 +1549,7 @@
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@@ -1561,7 +1561,7 @@
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@@ -1585,7 +1585,7 @@
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@@ -1596,7 +1596,7 @@
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@@ -1625,7 +1625,7 @@
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@@ -1636,7 +1636,7 @@
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@@ -1651,7 +1651,7 @@
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@@ -1668,7 +1668,7 @@
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@@ -1699,7 +1699,7 @@
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@@ -1711,7 +1711,7 @@
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@@ -1739,7 +1739,7 @@
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@@ -1769,7 +1769,7 @@
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@@ -1786,7 +1786,7 @@
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@@ -1798,7 +1798,7 @@
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@@ -1819,7 +1819,7 @@
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@@ -1832,7 +1832,7 @@
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@@ -1863,7 +1863,7 @@
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@@ -1875,7 +1875,7 @@
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@@ -1893,7 +1893,7 @@
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@@ -1920,7 +1920,7 @@
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@@ -1942,7 +1942,7 @@
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@@ -1980,7 +1980,7 @@
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@@ -1991,7 +1991,7 @@
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@@ -2004,7 +2004,7 @@
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@@ -2025,7 +2025,7 @@
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@@ -2037,7 +2037,7 @@
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@@ -2047,7 +2047,7 @@
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@@ -2059,7 +2059,7 @@
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@@ -2071,7 +2071,7 @@
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@@ -2083,7 +2083,7 @@
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@@ -2094,7 +2094,7 @@
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@@ -2106,7 +2106,7 @@
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@@ -2128,7 +2128,7 @@
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@@ -2140,7 +2140,7 @@
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@@ -2153,7 +2153,7 @@
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@@ -2170,7 +2170,7 @@
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@@ -2182,7 +2182,7 @@
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@@ -2192,7 +2192,7 @@
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@@ -2204,7 +2204,7 @@
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@@ -2214,7 +2214,7 @@
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@@ -2226,7 +2226,7 @@
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@@ -2236,7 +2236,7 @@
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@@ -2248,7 +2248,7 @@
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@@ -2264,7 +2264,7 @@
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@@ -2276,7 +2276,7 @@
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@@ -2287,7 +2287,7 @@
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@@ -2299,7 +2299,7 @@
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@@ -2313,7 +2313,7 @@
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@@ -2325,7 +2325,7 @@
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@@ -2350,7 +2350,7 @@
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@@ -2367,7 +2367,7 @@
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@@ -2411,7 +2411,7 @@
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@@ -2422,7 +2422,7 @@
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@@ -2444,7 +2444,7 @@
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@@ -2461,7 +2461,7 @@
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@@ -2482,7 +2482,7 @@
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@@ -2496,7 +2496,7 @@
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@@ -2525,7 +2525,7 @@
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@@ -2545,7 +2545,7 @@
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@@ -2562,7 +2562,7 @@
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@@ -2574,7 +2574,7 @@
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@@ -2592,7 +2592,7 @@
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@@ -2603,7 +2603,7 @@
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@@ -2616,7 +2616,7 @@
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@@ -2628,7 +2628,7 @@
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@@ -2659,7 +2659,7 @@
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@@ -2673,7 +2673,7 @@
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@@ -2713,7 +2713,7 @@
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@@ -2733,7 +2733,7 @@
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@@ -2765,7 +2765,7 @@
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@@ -2787,7 +2787,7 @@
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@@ -2815,7 +2815,7 @@
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@@ -2830,7 +2830,7 @@
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@@ -2842,7 +2842,7 @@
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@@ -2857,7 +2857,7 @@
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@@ -2870,7 +2870,7 @@
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@@ -2882,7 +2882,7 @@
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@@ -2892,7 +2892,7 @@
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@@ -2903,7 +2903,7 @@
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@@ -2921,7 +2921,7 @@
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@@ -2932,7 +2932,7 @@
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@@ -2944,7 +2944,7 @@
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@@ -2954,7 +2954,7 @@
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@@ -2966,7 +2966,7 @@
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@@ -2976,7 +2976,7 @@
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@@ -2988,7 +2988,7 @@
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@@ -2998,7 +2998,7 @@
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@@ -3017,7 +3017,7 @@
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@@ -3027,7 +3027,7 @@
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@@ -3039,7 +3039,7 @@
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@@ -3049,7 +3049,7 @@
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@@ -3065,7 +3065,7 @@
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@@ -3085,7 +3085,7 @@
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@@ -3095,7 +3095,7 @@
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@@ -3106,7 +3106,7 @@
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@@ -3125,7 +3125,7 @@
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@@ -3135,7 +3135,7 @@
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@@ -3147,7 +3147,7 @@
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@@ -3157,7 +3157,7 @@
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@@ -3168,7 +3168,7 @@
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@@ -3188,7 +3188,7 @@
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@@ -3200,7 +3200,7 @@
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@@ -3215,7 +3215,7 @@
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@@ -3295,7 +3295,7 @@
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@@ -3305,7 +3305,7 @@
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@@ -3317,7 +3317,7 @@
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@@ -3327,7 +3327,7 @@
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@@ -3338,7 +3338,7 @@
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@@ -3350,7 +3350,7 @@
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@@ -3360,7 +3360,7 @@
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@@ -3372,7 +3372,7 @@
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@@ -3382,7 +3382,7 @@
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@@ -3394,7 +3394,7 @@
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@@ -3407,7 +3407,7 @@
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@@ -3419,7 +3419,7 @@
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@@ -3429,7 +3429,7 @@
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@@ -3441,7 +3441,7 @@
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@@ -3453,7 +3453,7 @@
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@@ -3464,7 +3464,7 @@
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@@ -3476,7 +3476,7 @@
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@@ -3495,7 +3495,7 @@
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@@ -3508,7 +3508,7 @@
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@@ -3518,7 +3518,7 @@
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@@ -3530,7 +3530,7 @@
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@@ -3540,7 +3540,7 @@
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@@ -3552,7 +3552,7 @@
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@@ -3562,7 +3562,7 @@
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@@ -3574,7 +3574,7 @@
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@@ -3585,7 +3585,7 @@
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@@ -3597,7 +3597,7 @@
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@@ -3607,7 +3607,7 @@
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@@ -3619,7 +3619,7 @@
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@@ -3629,7 +3629,7 @@
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@@ -3641,7 +3641,7 @@
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@@ -3662,7 +3662,7 @@
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@@ -3676,7 +3676,7 @@
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@@ -3687,7 +3687,7 @@
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@@ -3699,7 +3699,7 @@
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@@ -3709,7 +3709,7 @@
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@@ -3721,7 +3721,7 @@
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@@ -3731,7 +3731,7 @@
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@@ -3743,7 +3743,7 @@
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@@ -3755,7 +3755,7 @@
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@@ -3769,7 +3769,7 @@
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@@ -3784,7 +3784,7 @@
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@@ -3795,7 +3795,7 @@
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@@ -3808,7 +3808,7 @@
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@@ -3819,7 +3819,7 @@
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@@ -3842,7 +3842,7 @@
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@@ -3856,7 +3856,7 @@
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@@ -3869,7 +3869,7 @@
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@@ -3880,7 +3880,7 @@
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@@ -3892,7 +3892,7 @@
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@@ -3903,7 +3903,7 @@
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@@ -3919,7 +3919,7 @@
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@@ -3930,7 +3930,7 @@
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@@ -3944,7 +3944,7 @@
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@@ -3966,7 +3966,7 @@
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@@ -3978,7 +3978,7 @@
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@@ -3988,7 +3988,7 @@
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@@ -4000,7 +4000,7 @@
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@@ -4012,7 +4012,7 @@
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@@ -4022,7 +4022,7 @@
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@@ -4034,7 +4034,7 @@
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@@ -4044,7 +4044,7 @@
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@@ -4056,7 +4056,7 @@
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@@ -4066,7 +4066,7 @@
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@@ -4078,7 +4078,7 @@
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@@ -4090,7 +4090,7 @@
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@@ -4100,7 +4100,7 @@
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@@ -4112,7 +4112,7 @@
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@@ -4122,7 +4122,7 @@
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@@ -4134,7 +4134,7 @@
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@@ -4146,7 +4146,7 @@
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@@ -4158,7 +4158,7 @@
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@@ -4168,7 +4168,7 @@
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@@ -4180,7 +4180,7 @@
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@@ -4190,7 +4190,7 @@
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@@ -4202,7 +4202,7 @@
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@@ -4212,7 +4212,7 @@
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@@ -4224,7 +4224,7 @@
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@@ -4235,7 +4235,7 @@
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@@ -4247,7 +4247,7 @@
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@@ -4257,7 +4257,7 @@
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@@ -4269,7 +4269,7 @@
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@@ -4279,7 +4279,7 @@
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@@ -4291,7 +4291,7 @@
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@@ -4304,7 +4304,7 @@
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@@ -4316,7 +4316,7 @@
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@@ -4328,7 +4328,7 @@
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@@ -4340,7 +4340,7 @@
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@@ -4352,7 +4352,7 @@
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@@ -4364,7 +4364,7 @@
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@@ -4374,7 +4374,7 @@
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@@ -4386,7 +4386,7 @@
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@@ -4398,7 +4398,7 @@
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@@ -4411,7 +4411,7 @@
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@@ -4438,7 +4438,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "75e1f4b7",
+   "id": "6b751c2d",
    "metadata": {
     "editable": true
    },
@@ -4449,7 +4449,7 @@
   {
    "cell_type": "code",
    "execution_count": 44,
-   "id": "85558d22",
+   "id": "bb73d152",
    "metadata": {
     "collapsed": false,
     "editable": true
@@ -4545,7 +4545,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9c77051b",
+   "id": "a6c0341d",
    "metadata": {
     "editable": true
    },
@@ -4560,7 +4560,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "dcd7fd6c",
+   "id": "0d40224a",
    "metadata": {
     "editable": true
    },
@@ -4582,7 +4582,7 @@
   {
    "cell_type": "code",
    "execution_count": 45,
-   "id": "8acb8b60",
+   "id": "ed0c252a",
    "metadata": {
     "collapsed": false,
     "editable": true
@@ -4657,7 +4657,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "1683d250",
+   "id": "bb0e0950",
    "metadata": {
     "editable": true
    },
@@ -4669,7 +4669,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "80d8bbf9",
+   "id": "b903607d",
    "metadata": {
     "editable": true
    },
@@ -4738,7 +4738,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b6c703df",
+   "id": "3e5382a1",
    "metadata": {
     "editable": true
    },
@@ -4752,7 +4752,7 @@
   {
    "cell_type": "code",
    "execution_count": 46,
-   "id": "3424ebd0",
+   "id": "b9efaacc",
    "metadata": {
     "collapsed": false,
     "editable": true
@@ -4765,7 +4765,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a29ae2f0",
+   "id": "dad5e434",
    "metadata": {
     "editable": true
    },
@@ -4779,7 +4779,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "79b37147",
+   "id": "220c0b8b",
    "metadata": {
     "editable": true
    },
@@ -4792,7 +4792,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "42e32d0b",
+   "id": "baf69d5c",
    "metadata": {
     "editable": true
    },
@@ -4803,7 +4803,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4e2b4915",
+   "id": "9b8f51aa",
    "metadata": {
     "editable": true
    },
@@ -4815,7 +4815,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2a1b4858",
+   "id": "e7ecf40d",
    "metadata": {
     "editable": true
    },
@@ -4825,7 +4825,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5553027d",
+   "id": "060cc029",
    "metadata": {
     "editable": true
    },
@@ -4837,7 +4837,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3a717a9d",
+   "id": "01d833b9",
    "metadata": {
     "editable": true
    },
@@ -4848,7 +4848,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7112faa9",
+   "id": "91a24338",
    "metadata": {
     "editable": true
    },
@@ -4867,7 +4867,7 @@
   {
    "cell_type": "code",
    "execution_count": 47,
-   "id": "0b17e9a8",
+   "id": "d2ea920d",
    "metadata": {
     "collapsed": false,
     "editable": true
@@ -4883,7 +4883,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5edbcf8b",
+   "id": "315e8f30",
    "metadata": {
     "editable": true
    },
@@ -4893,7 +4893,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5a89a327",
+   "id": "c0c2b0a4",
    "metadata": {
     "editable": true
    },
@@ -4904,7 +4904,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "cad4cff7",
+   "id": "b5cc5079",
    "metadata": {
     "editable": true
    },
@@ -4915,7 +4915,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a61d665d",
+   "id": "bf0d626d",
    "metadata": {
     "editable": true
    },
diff --git a/doc/src/week34/week34.do.txt b/doc/src/week34/week34.do.txt
index 242af6c3a..42f2a8802 100644
--- a/doc/src/week34/week34.do.txt
+++ b/doc/src/week34/week34.do.txt
@@ -250,7 +250,7 @@ specifically, after this course you will
 * Learn about about decision trees, random forests, bagging and boosting methods;
 * Learn about support vector machines and kernel transformations;
 * Reduction of data sets, from PCA to clustering;
-* Autoencoders and Reinforcement Learning;
+* Generative models
 * Work on numerical projects to illustrate the theory. The projects play a central role and you are expected to know modern programming languages like Python or C++ and/or Fortran (Fortran2003 or later) or Julia or other.
 
 !eblock