links to new blackboard course

index.Rmd

@@ -28,7 +28,7 @@ Assessment: Assignments and Exam  <br>
 
 ---
 
-All practicals and assignments should be hand in [via blackboard](https://uu.blackboard.com/webapps/blackboard/content/listContentEditable.jsp?content_id=_4472168_1&course_id=_146275_1&mode=reset)
+All practicals and assignments should be hand in [via blackboard](https://uu.blackboard.com/webapps/blackboard/execute/announcement?method=search&context=course&course_id=_152615_1&handle=cp_announcements&mode=cpview)
 
 ---
 
@@ -78,11 +78,11 @@ In order to pass the course, the final grade must be 5.5 or higher, your contrib
 |--------|---------------------|--------|-----------|------|
 | 1 | Data wrangling with `R` and the grammar of graphics | `tidyverse: filter(), select(), join(), pivot(), dbplyr`, `ggplot()`: `geoms`, `aesthetics`, `scales`, `themes` | [R4DS](https://r4ds.had.co.nz) | DG |
 | 2 | Exploratory data analysis | `Histograms`, `density plots`, `boxplots`, etc. | [R4DS](https://r4ds.had.co.nz) [FIMD Ch1](https://stefvanbuuren.name/fimd/ch-introduction.html) | MC | 
-| 3 | Statistical learning: regression | `lm()`, `glm()`, `knn()` | [ISLR](https://www.statlearning.com/) | DG |
+| 3 | Statistical learning: regression | `lm()`, `glm()`, `knn()` | [ISLR](https://www.statlearning.com/) | MC |
 | 4 | Statistical learning: classification | `glm()`, trees, `lda()` | [ISLR](https://www.statlearning.com/) | EJvK |
 | 5 | Classification model evaluation | `prop.table()`, `pROC()`, etc. | [ISLR](https://www.statlearning.com/) | EJvK |
 |	6 | Nonlinear models | `R` formulas advanced: `I()`, splines, e.g., `bs()` | [ISLR](https://www.statlearning.com/) | MC |
-| 7 | Bagging, boosting, random forest and support vector machines | `randomforest`, `xgboost` | [ISLR](https://www.statlearning.com/) | MC |
+| 7 | Bagging, boosting, random forest and support vector machines | `randomforest`, `xgboost` | [ISLR](https://www.statlearning.com/) | DG |
 | 8 | Benchmarking | `mlr3verse` | [ISLR](https://www.statlearning.com/) [mlr3-book](https://mlr3book.mlr-org.com/) | DG |
 
 <!-- | 5 | Regression model evaluation | model comparison with cross-validation | ISLR |  -->
@@ -109,7 +109,7 @@ Students will learn to adapt these techniques in their way of thinking about ana
 
 
 ### Assignments
-Students will form groups to choose work on two assignments. Students will need to perform calculations and program code for these assignments. All work needs to be combined in an easy understandable, self-contained and insightful `RStudio` project and must be submitted to the [course Blackboard page](). Each assignment will be graded. 
+Students will form groups to choose work on two assignments. Students will need to perform calculations and program code for these assignments. All work needs to be combined in an easy understandable, self-contained and insightful `RStudio` project and must be submitted to the [course Blackboard page](https://uu.blackboard.com/webapps/blackboard/execute/announcement?method=search&context=course&course_id=_152615_1&handle=cp_announcements&mode=cpview). Each assignment will be graded. 
 
 ### Grading
 Students will be evaluated on the following aspects:
@@ -240,7 +240,7 @@ This week's practical is split into two parts - *practical 1* on data wrangling
 - [Practical 1b: Data visualization with code solutions](practicals/02_Data_Visualization/02_Data_Visualisation_answers.html)
 
 
-Hand in your answers to both practicals separately [via blackboard]().
+Hand in your answers to both practicals separately [via blackboard](https://uu.blackboard.com/webapps/blackboard/execute/announcement?method=search&context=course&course_id=_152615_1&handle=cp_announcements&mode=cpview).
 
 ### A must watch
 The below 4-part series by Garrett Grolemund on `dplyr` and the `tidyverse` is very informative:
@@ -295,7 +295,7 @@ This week's practical is on exploratory data analysis. Code solutions are also g
 - [Practical 2: EDA](practicals/03_Exploratory/03_Exploratory.html)
 - [Practical 2: EDA with code solutions](practicals/03_Exploratory/03_Exploratory_Answers.html)
 
-Hand in [via blackboard]().
+Hand in [via blackboard](https://uu.blackboard.com/webapps/blackboard/execute/announcement?method=search&context=course&course_id=_152615_1&handle=cp_announcements&mode=cpview).
 
 ## Column 2
 
@@ -337,7 +337,7 @@ This week's practical is on regression. Code solutions are also given to you. Us
 - [Practical 3: Regression](practicals/04_Regression/04_Regression.html)
 - [Practical 3: Regression with code solutions](practicals/04_Regression/04_Regression_answers.html)
 
-Hand in [via blackboard]().
+Hand in [via blackboard](https://uu.blackboard.com/webapps/blackboard/execute/announcement?method=search&context=course&course_id=_152615_1&handle=cp_announcements&mode=cpview).
 
 ## Column 2
 
@@ -365,7 +365,7 @@ This week's practical is on classification. Code solutions are also given to you
 - [Practical 4: Classification answers](practicals/06_classification/06_classification_answers.html)
 - [data](practicals/06_classification/data.zip)
 
-Hand in [via blackboard]().
+Hand in [via blackboard](https://uu.blackboard.com/webapps/blackboard/execute/announcement?method=search&context=course&course_id=_152615_1&handle=cp_announcements&mode=cpview).
 
 **NOT HAND IN, BUT STILL USEFUL**: I also give you the following practical from last year. Please view and study the practical up to and including Exercise 10. No need to hand anything in. All the regularization (`glmnet`) exercises 11-19 are not specifically covered in this course, but you may of course use the methods in your Assignment 2 if you wish. Let us know if you have any questions. 
 
@@ -398,7 +398,7 @@ This week's practical is on classification. Code solutions are also given to you
 - [Practical 5: Classification evaluation answers](practicals/07_classification_evaluation/07_classification_evaluation_answers.html)
 - [data](practicals/07_classification_evaluation/data.zip)
 
-Hand in [via blackboard]().
+Hand in [via blackboard](https://uu.blackboard.com/webapps/blackboard/execute/announcement?method=search&context=course&course_id=_152615_1&handle=cp_announcements&mode=cpview).
 
 ## Column 2
 
@@ -424,7 +424,7 @@ This week's practical is on nonlinear regression. Code solutions are also given
 - [Practical 6: Nonlinear regression](practicals/08_nonlinear_regression/08_nonlinear_regression.html)
 - [Practical 6: Nonlinear regression answers](practicals/08_nonlinear_regression/08_nonlinear_regression_answers.html)
 
-Hand in [via blackboard]().
+Hand in [via blackboard](https://uu.blackboard.com/webapps/blackboard/execute/announcement?method=search&context=course&course_id=_152615_1&handle=cp_announcements&mode=cpview).
 
 ## Column 2
 
@@ -451,7 +451,7 @@ This week's practical is on nonlinear regression. Code solutions are also given
 - [Practical 7: Tree-based methods and SVM answers](practicals/09_ensemble/09_ensemble_answers.html)
 - [Data](practicals/09_ensemble/data.zip)
 
-Hand in [via blackboard]().
+Hand in [via blackboard](https://uu.blackboard.com/webapps/blackboard/execute/announcement?method=search&context=course&course_id=_152615_1&handle=cp_announcements&mode=cpview).
 
 ## Column 2
 
@@ -477,7 +477,7 @@ This week's practical is about conducting ML benchmarks with `mlr3`. Code soluti
 - [Practical 8: ML Benchmark answers](practicals/10-benchmark/10_benchmark_answers.html)
 - [Data](practicals/10-benchmark/data.zip)
 
-Hand in [via blackboard]().
+Hand in [via blackboard](https://uu.blackboard.com/webapps/blackboard/execute/announcement?method=search&context=course&course_id=_152615_1&handle=cp_announcements&mode=cpview).
 
 
 

index.html

@@ -1925,7 +1925,7 @@ <h1 class="sidebar">Intro</h1>
 Exam <br></p>
 <hr />
 <p>All practicals and assignments should be hand in <a
-href="https://uu.blackboard.com/webapps/blackboard/content/listContentEditable.jsp?content_id=_4472168_1&amp;course_id=_146275_1&amp;mode=reset">via
+href="https://uu.blackboard.com/webapps/blackboard/execute/announcement?method=search&amp;context=course&amp;course_id=_152615_1&amp;handle=cp_announcements&amp;mode=cpview">via
 blackboard</a></p>
 <hr />
 <p><strong>LECTURES:</strong></p>
@@ -2099,7 +2099,7 @@ <h3>Schedule</h3>
 <td>Statistical learning: regression</td>
 <td><code>lm()</code>, <code>glm()</code>, <code>knn()</code></td>
 <td><a href="https://www.statlearning.com/">ISLR</a></td>
-<td>DG</td>
+<td>MC</td>
 </tr>
 <tr class="even">
 <td>4</td>
@@ -2128,7 +2128,7 @@ <h3>Schedule</h3>
 <td>Bagging, boosting, random forest and support vector machines</td>
 <td><code>randomforest</code>, <code>xgboost</code></td>
 <td><a href="https://www.statlearning.com/">ISLR</a></td>
-<td>MC</td>
+<td>DG</td>
 </tr>
 <tr class="even">
 <td>8</td>
@@ -2193,8 +2193,9 @@ <h3>Assignments</h3>
 will need to perform calculations and program code for these
 assignments. All work needs to be combined in an easy understandable,
 self-contained and insightful <code>RStudio</code> project and must be
-submitted to the <a href="">course Blackboard page</a>. Each assignment
-will be graded.</p>
+submitted to the <a
+href="https://uu.blackboard.com/webapps/blackboard/execute/announcement?method=search&amp;context=course&amp;course_id=_152615_1&amp;handle=cp_announcements&amp;mode=cpview">course
+Blackboard page</a>. Each assignment will be graded.</p>
 </div>
 <div id="grading" class="section level3">
 <h3>Grading</h3>
@@ -2416,7 +2417,8 @@ <h3>Practical</h3>
 href="practicals/02_Data_Visualization/02_Data_Visualisation_answers.html">Practical
 1b: Data visualization with code solutions</a></p></li>
 </ul>
-<p>Hand in your answers to both practicals separately <a href="">via
+<p>Hand in your answers to both practicals separately <a
+href="https://uu.blackboard.com/webapps/blackboard/execute/announcement?method=search&amp;context=course&amp;course_id=_152615_1&amp;handle=cp_announcements&amp;mode=cpview">via
 blackboard</a>.</p>
 </div>
 <div id="a-must-watch" class="section level3">
@@ -2499,7 +2501,9 @@ <h3>Practical</h3>
 href="practicals/03_Exploratory/03_Exploratory_Answers.html">Practical
 2: EDA with code solutions</a></li>
 </ul>
-<p>Hand in <a href="">via blackboard</a>.</p>
+<p>Hand in <a
+href="https://uu.blackboard.com/webapps/blackboard/execute/announcement?method=search&amp;context=course&amp;course_id=_152615_1&amp;handle=cp_announcements&amp;mode=cpview">via
+blackboard</a>.</p>
 </div>
 </div>
 <div id="column-2-3" class="section level2">
@@ -2565,7 +2569,9 @@ <h3>Practical</h3>
 href="practicals/04_Regression/04_Regression_answers.html">Practical 3:
 Regression with code solutions</a></li>
 </ul>
-<p>Hand in <a href="">via blackboard</a>.</p>
+<p>Hand in <a
+href="https://uu.blackboard.com/webapps/blackboard/execute/announcement?method=search&amp;context=course&amp;course_id=_152615_1&amp;handle=cp_announcements&amp;mode=cpview">via
+blackboard</a>.</p>
 </div>
 </div>
 <div id="column-2-4" class="section level2">
@@ -2603,7 +2609,9 @@ <h3>Practical</h3>
 4: Classification answers</a></li>
 <li><a href="practicals/06_classification/data.zip">data</a></li>
 </ul>
-<p>Hand in <a href="">via blackboard</a>.</p>
+<p>Hand in <a
+href="https://uu.blackboard.com/webapps/blackboard/execute/announcement?method=search&amp;context=course&amp;course_id=_152615_1&amp;handle=cp_announcements&amp;mode=cpview">via
+blackboard</a>.</p>
 <p><strong>NOT HAND IN, BUT STILL USEFUL</strong>: I also give you the
 following practical from last year. Please view and study the practical
 up to and including Exercise 10. No need to hand anything in. All the
@@ -2659,7 +2667,9 @@ <h3>Practical</h3>
 <li><a
 href="practicals/07_classification_evaluation/data.zip">data</a></li>
 </ul>
-<p>Hand in <a href="">via blackboard</a>.</p>
+<p>Hand in <a
+href="https://uu.blackboard.com/webapps/blackboard/execute/announcement?method=search&amp;context=course&amp;course_id=_152615_1&amp;handle=cp_announcements&amp;mode=cpview">via
+blackboard</a>.</p>
 </div>
 </div>
 <div id="column-2-6" class="section level2">
@@ -2699,7 +2709,9 @@ <h3>Practical</h3>
 href="practicals/08_nonlinear_regression/08_nonlinear_regression_answers.html">Practical
 6: Nonlinear regression answers</a></li>
 </ul>
-<p>Hand in <a href="">via blackboard</a>.</p>
+<p>Hand in <a
+href="https://uu.blackboard.com/webapps/blackboard/execute/announcement?method=search&amp;context=course&amp;course_id=_152615_1&amp;handle=cp_announcements&amp;mode=cpview">via
+blackboard</a>.</p>
 </div>
 </div>
 <div id="column-2-7" class="section level2">
@@ -2737,7 +2749,9 @@ <h3>Practical</h3>
 7: Tree-based methods and SVM answers</a></li>
 <li><a href="practicals/09_ensemble/data.zip">Data</a></li>
 </ul>
-<p>Hand in <a href="">via blackboard</a>.</p>
+<p>Hand in <a
+href="https://uu.blackboard.com/webapps/blackboard/execute/announcement?method=search&amp;context=course&amp;course_id=_152615_1&amp;handle=cp_announcements&amp;mode=cpview">via
+blackboard</a>.</p>
 </div>
 </div>
 <div id="column-2-8" class="section level2">
@@ -2777,7 +2791,9 @@ <h3>Practical</h3>
 Benchmark answers</a></li>
 <li><a href="practicals/10-benchmark/data.zip">Data</a></li>
 </ul>
-<p>Hand in <a href="">via blackboard</a>.</p>
+<p>Hand in <a
+href="https://uu.blackboard.com/webapps/blackboard/execute/announcement?method=search&amp;context=course&amp;course_id=_152615_1&amp;handle=cp_announcements&amp;mode=cpview">via
+blackboard</a>.</p>
 </div>
 </div>
 <div id="column-2-9" class="section level2">

lectures/L10/Lecture 10.Rmd

@@ -449,3 +449,5 @@ mlr3viz::autoplot(results, measure = msr("classif.acc"), type = "boxplot")
     - most comprehensive ecosystem in R that is constantly updated
 
 - More detailed descriptions and tutorials to deal with more advanced problems can be found under https://mlr3.mlr-org.com/ 
+
+- Other popular frameworks include `tidymodels` (https://www.tidymodels.org/), `caret` (https://topepo.github.io/caret/), or `h2o` (https://cran.r-project.org/web/packages/h2o/index.html)

practicals/01_Data_Wrangling/01_Data_Wrangling.Rmd

@@ -1,8 +1,8 @@
 ---
 title: "Data wrangling"
 params:
-  #answers: true # uncomment if answers are to be included
-  answers: false
+  answers: true # uncomment if answers are to be included
+  #answers: false
 mainfont: Arial
 fontsize: 12pt
 urlcolor: blue
@@ -14,7 +14,7 @@ output:
     df_print: paged
     theme: paper
     highlight: pygments
-    #pandoc_args: --output=01_Data_Wrangling_Answers.html # uncomment if answers are to be included
+    pandoc_args: --output=01_Data_Wrangling_Answers.html # uncomment if answers are to be included
 ---
 
 ---
@@ -438,6 +438,6 @@ read_csv("data/googleplaystore.csv") %>%
 When you have finished the practical, 
 
 
-- enclose all files of the project `01_Data_wrangling.Rproj` (i.e. all `.R` and/or `.Rmd` files including the one with your answers, and the `.Rproj` file) in a zip file, and 
+- enclose all files of the project (i.e. all `.R` and/or `.Rmd` files including the one with your answers, and the `.Rproj` file) in a zip file, and 
 
-- hand in the zip [here](https://uu.blackboard.com/webapps/blackboard/content/listContentEditable.jsp?content_id=_4472168_1&course_id=_146275_1&mode=reset). Do so before Lecture 3. That way we can iron out issues during the next Q&A in Week 2. 
+- hand in the zip [here](https://uu.blackboard.com/webapps/blackboard/content/listContentEditable.jsp?content_id=_4935396_1&course_id=_152615_1&mode=reset). Do so before next week's lecture. 

practicals/02_Data_Visualization/02_Data_Visualisation_answers.html

@@ -2592,7 +2592,7 @@
 </style>
 <style type="text/css" data-origin="pandoc">
 pre > code.sourceCode { white-space: pre; position: relative; }
-pre > code.sourceCode > span { display: inline-block; line-height: 1.25; }
+pre > code.sourceCode > span { line-height: 1.25; }
 pre > code.sourceCode > span:empty { height: 1.2em; }
 .sourceCode { overflow: visible; }
 code.sourceCode > span { color: inherit; text-decoration: inherit; }
@@ -3361,12 +3361,11 @@ <h1>Final exercise</h1>
 <h1>Hand-in</h1>
 <p>When you have finished the practical,</p>
 <ul>
-<li><p>enclose all files of the project
-<code>02_Data_Visualization.Rproj</code> (i.e. all <code>.R</code>
-and/or <code>.Rmd</code> files including the one with your answers, and
-the <code>.Rproj</code> file) in a zip file, and</p></li>
-<li><p>hand in the zip <a href="https://uu.blackboard.com/webapps/blackboard/content/listContentEditable.jsp?content_id=_4472168_1&amp;course_id=_146275_1&amp;mode=reset">here</a>.
-Do so before Lecture 3.</p></li>
+<li><p>enclose all files of the project (i.e. all <code>.R</code> and/or
+<code>.Rmd</code> files including the one with your answers, and the
+<code>.Rproj</code> file) in a zip file, and</p></li>
+<li><p>hand in the zip <a href="https://uu.blackboard.com/webapps/blackboard/content/listContentEditable.jsp?content_id=_4935396_1&amp;course_id=_152615_1&amp;mode=reset">here</a>.
+Do so before next week’s lecture.</p></li>
 </ul>
 </div>
 

practicals/02_Data_Visualization/02_Data_Visualization.Rmd

@@ -1,8 +1,8 @@
 ---
 title: "Data Visualisation using ggplot2"
 params:
-  answers: true # uncomment if answers are to be included
-  # answers: false #uncomment if answers are not to be included
+  # answers: true # uncomment if answers are to be included
+  answers: false #uncomment if answers are not to be included
 mainfont: Arial
 fontsize: 12pt
 urlcolor: blue
@@ -14,7 +14,7 @@ output:
     df_print: paged
     theme: paper
     highlight: pygments
-    pandoc_args: --output=02_Data_Visualisation_answers.html # uncomment if answers are to be included
+    # pandoc_args: --output=02_Data_Visualisation_answers.html # uncomment if answers are to be included
 ---
 
 # Introduction
@@ -485,6 +485,6 @@ Carseats %>%
 When you have finished the practical, 
 
 
-- enclose all files of the project `02_Data_Visualization.Rproj` (i.e. all `.R` and/or `.Rmd` files including the one with your answers, and the `.Rproj` file) in a zip file, and 
+- enclose all files of the project (i.e. all `.R` and/or `.Rmd` files including the one with your answers, and the `.Rproj` file) in a zip file, and 
 
-- hand in the zip [here](https://uu.blackboard.com/webapps/blackboard/content/listContentEditable.jsp?content_id=_4472168_1&course_id=_146275_1&mode=reset). Do so before Lecture 3.
+- hand in the zip [here](https://uu.blackboard.com/webapps/blackboard/content/listContentEditable.jsp?content_id=_4935396_1&course_id=_152615_1&mode=reset). Do so before next week's lecture.

practicals/03_Exploratory/03_Exploratory.Rmd

@@ -445,7 +445,7 @@ When you have finished the practical,
 
 - enclose all files of the project (i.e. all `.R` and/or `.Rmd` files including the one with your answers, and the `.Rproj` file) in a zip file or folder, and 
 
-- hand in that zip [here](https://uu.blackboard.com/webapps/blackboard/content/listContentEditable.jsp?content_id=_4472168_1&course_id=_146275_1&mode=reset). Do so before Lecture 4. 
+- hand in the zip [here](https://uu.blackboard.com/webapps/blackboard/content/listContentEditable.jsp?content_id=_4935396_1&course_id=_152615_1&mode=reset). Do so before next week's lecture. 
 
 ---
 

practicals/04_Regression/04_Regression.Rmd

@@ -1,7 +1,7 @@
 ---
 title: "Supervised learning: Regression 1"
 params:
-  answers: true
+  answers: false
 mainfont: Arial
 fontsize: 12pt
 urlcolor: blue
@@ -13,7 +13,7 @@ output:
     df_print: paged
     theme: paper
     highlight: pygments
-    pandoc_args: --output=04_Regression_answers.html
+    #pandoc_args: --output=04_Regression_answers.html
 ---
 
 ```{r global_options, include=FALSE}
@@ -585,8 +585,8 @@ cv_lm(formula = medv ~ lstat + I(lstat^2) + age + tax, dataset = Boston, k = 9)
 When you have finished the practical, 
 
 
-- enclose all files of the project `04_Regression.Rproj` (i.e. all `.R` and/or `.Rmd` files including the one with your answers, and the `.Rproj` file) in a zip file, and 
+- enclose all files of the project (i.e. all `.R` and/or `.Rmd` files including the one with your answers, and the `.Rproj` file) in a zip file, and 
 
-- hand in the zip [here](https://uu.blackboard.com/webapps/blackboard/content/listContentEditable.jsp?content_id=_4472168_1&course_id=_146275_1&mode=reset). Do so before Lecture 6.
+- hand in the zip [here](https://uu.blackboard.com/webapps/blackboard/content/listContentEditable.jsp?content_id=_4935396_1&course_id=_152615_1&mode=reset). Do so before next week's lecture. 
 
 ---