update

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>

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>

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>

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>

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