EDIT 2024-05-14: Bernd asked for a fix to the title block where the chunk is split from the section title, e.g. the chunk "CART" is fixed as a separate argument. Examples will be updated next. EDIT 2024-05-15: The separating : is now omitted as per Bernd's request. I did not bother updating the example screenshot though.

This now adds a \titlemeta macro, example usage:

[...]

\title{Introduction to Machine Learning}

\begin{document}

\titlemeta{% Chunk title (example: CART, Forests, Boosting, ...), can be empty
    CART 
  }{% Lecture title  
    Advantages \& Disadvantages 
  }{% Relative path to title page image: Can be empty but must not start with slides/
  figure/cart_dis_1
  }{
  \item Understand the advantages and disadvantages of CART
  \item Know when and where CART are applied
}

\begin{vbframe}{Second Slide}
[...]

Notably the 1st, 3rd and 4th argument can be empty but must be passed, e.g. the following would be valid.

\titlemeta{% Chunk title (example: CART, Forests, Boosting, ...), can be empty
  }{% Lecture title  
    Advantages \& Disadvantages 
  }{% Relative path to title page image: Can be empty but must not start with slides/
  }{
}

If the chunk title (CART) is ommited, the lecture title is displayed on its own without a linebreak.
- -> This is relevant for single-slide-topics such as knn
If the title figure is ommitted, the learning goals are horizontally centered
If the learning goals are omitted, the title figure is horizontally centered

Since title figure caption are used exceedingly rarely, I did not bother making that an additional argument since latex macros aren't exactly ergonomic when it comes to these things, so the old approach of declaring an ad-hoc command with the caption is still valid, see e.g. ml-basics/slides-basics-whatisml.tex:

\newcommand{\titlecaption}{\tiny Image via \url{www.vpnsrus.com}}

For this to be usable every single slide has to be switched over or everything breaks.

Lecture Slide Status Overview

2024-05-17 14:26:49 CEST

lecture_i2ml

This is a reduced version of the full status check rendered for each lecture repository.
It does not link to rendered PDF files and only produces markdown tables, which allows it to be appended to a pull request. It serves as a rough check to ensure that the PR does not cause major breakage.

Branch	Last Commit	By	Message
main	2024-05-17 12:13:04	Lukas Burk	Fix textcase tex dep

Status of the lecture_service repo (time in UTC)

Lecture	Branch	Last Commit	By	Message
lecture_i2ml	?	2024-05-17 12:21:22	GitHub	Merge 817239347daa19140ed341f05c61d96b64ba8f06 into c55f4cf315cda18512e9153e88ca3fb76f427ecc

Latest commits per lecture (times in UTC)

lecture_i2ml

11 topics with a total of 67 slides

compile_check	n
✅	67

compile_check	compare_check	n
✅		3
✅	✅	34
✅	❌	3
✅	❓	27

cart

Slide	Compiles?	Comparison
slides-cart-computationalaspects	✅	✅
slides-cart-discussion	✅	✅
slides-cart-nutshell	✅	✅
slides-cart-predictions	✅	✅
slides-cart-splitcriteria-classification	✅	✅
slides-cart-splitcriteria-regression	✅	✅
slides-cart-stoppingpruning	✅	✅
slides-cart-treegrowing	✅	✅

evaluation

Slide	Compiles?	Comparison	Note
slides-evaluation-auc-mwu	✅	✅
slides-evaluation-generr	✅	❓	Dissimilar pages: 3, 8, 9
slides-evaluation-mcauc	✅	✅
slides-evaluation-measures-classification	✅	✅
slides-evaluation-measures-regression	✅	✅
slides-evaluation-nutshell	✅	❓	Dissimilar pages: 7, 10
slides-evaluation-overfitting-underfitting	✅	✅
slides-evaluation-partialauc	✅	✅
slides-evaluation-prcurves	✅	✅
slides-evaluation-resampling-1	✅	❓	Dissimilar pages: 2, 3
slides-evaluation-resampling-2	✅	❓	Dissimilar pages: 5, 6, 7, 10
slides-evaluation-rocbasics	✅	✅
slides-evaluation-roccurves	✅	❓	Dissimilar pages: 6
slides-evaluation-test	✅	❓	Dissimilar pages: 2
slides-evaluation-train	✅	❓	Dissimilar pages: 2, 4

forests

Slide	Compiles?	Comparison	Note
slides-forests-bagging	✅	❓	Dissimilar pages: 1
slides-forests-benchmark	✅	❓	Dissimilar pages: 1
slides-forests-discussion	✅	❓	Dissimilar pages: 1
slides-forests-featureimportance	✅	❓	Dissimilar pages: 1
slides-forests-intro	✅	❓	Dissimilar pages: 1
slides-forests-nutshell	✅	❓	Dissimilar pages: 1
slides-forests-proximities	✅	❓	Dissimilar pages: 1

knn

Slide	Compiles?	Comparison	Note
slides-knn	✅	✅

ml-basics

Slide	Compiles?	Comparison	Note
slides-basics-data	✅	❓	Dissimilar pages: 8
slides-basics-learner	✅	✅
slides-basics-learnercomponents-hro	✅	✅
slides-basics-models-parameters	✅	✅
slides-basics-nutshell	✅	❓	Dissimilar pages: 6
slides-basics-optimization	✅	❓	Dissimilar pages: 11
slides-basics-riskminimization	✅	❓	Dissimilar pages: 3, 7, 9, 10
slides-basics-task	✅	✅
slides-basics-whatisml	✅	✅

ml-philosophy

Slide	Compiles?	Comparison	Note
slides-mlphilo-2cultures	✅		No reference PDF
slides-mlphilo-blackboxes	✅	✅
slides-mlphilo-computerscience	✅		No reference PDF
slides-mlphilo-ontology	✅		No reference PDF

nested-resampling

Slide	Compiles?	Comparison
slides-nested-nestedintro	✅	✅
slides-nested-nestedresampling	✅	✅
slides-nested-trainvalidtest	✅	✅

neural-networks

Slide	Compiles?	Comparison	Note
slides-nn-nutshell	✅	✅

supervised-classification

Slide	Compiles?	Comparison	Note
slides-classification-basicdefs	✅	❓	Dissimilar pages: 11
slides-classification-discranalysis	✅	❓	Dissimilar pages: 6
slides-classification-linear	✅	❓	Dissimilar pages: 2, 3
slides-classification-logistic	✅	✅
slides-classification-naivebayes	✅	❓	Dissimilar pages: 2
slides-classification-nutshell	✅	✅
slides-classification-tasks	✅	❓	Dissimilar pages: 7

supervised-regression

Slide	Compiles?	Comparison	Note
slides-regression-deepdive-ols	✅	✅
slides-regression-linearmodel-l1	✅	❓	Dissimilar pages: 6
slides-regression-linearmodel-l2	✅	❓	Dissimilar pages: 2, 6, 14
slides-regression-nutshell	✅	❓	Dissimilar pages: 3, 4, 5
slides-regression-polynomials	✅	❓	Dissimilar pages: 5

tuning

Slide	Compiles?	Comparison	Note
slides-tuning-advanced	✅	❌	Differing page count: 15 vs 14
slides-tuning-basicalgos	✅	✅
slides-tuning-intro	✅	❌	Differing page count: 9 vs 8
slides-tuning-nutshell	✅	✅
slides-tuning-pipelines	✅	✅
slides-tuning-practical	✅	❌	Differing page count: 8 vs 6
slides-tuning-tuningproblem	✅	✅

slds-lmu / lecture_i2ml

New title slide macro #1211