Merge pull request #544 from compstat-lmu/basic-concepts-lisa-highimpact

Fixes to chapter 1 (wording, visualizations)

.gitignore

@@ -15,12 +15,8 @@
 .Rproj.user
 .Rproj.user/
 cache/
-figure/
 docs/
 
-slides/*/slides*.pdf
-slides*.tex
-
 exercise_*.pdf
 exercise_*.tex
 

CHANGELOG.md

@@ -1,2 +1,13 @@
 ## Changelog
+
+### 11-2020
+- Reworked Chapter 1: 
+    - Concepts are now in clear, single chunks
+    - New chunk on optimization
+
+### 10-2020
+- Switch from mlr to mlr3
+
+
+### 09-2020
 - Rnw-files split into pure tex-files and figure producing R-files

CONTRIBUTING.md

@@ -63,6 +63,10 @@ what material needs to be understood before what else. Please do add appropriate
 
 now in `/code-demos`. Originals at [this link](https://github.com/compstat-lmu/lecture_intro_to_ml_notebooks)
 
+### Google Figures
+
+Google Figures are stored in the [G-Drive](https://drive.google.com/drive/folders/1JVlK94X7-h1DNaUo-gxOvIyVZph42iHj)
+
 ### Creating Lecture Videos
 
 - Video files should have the same name as the slide set they are narrating.

README.md

@@ -1,6 +1,6 @@
 # Introduction to Machine Learning (I2ML)
 
-Main course site: https://compstat-lmu.github.io/lecture_i2ml
+Main course site: https://introduction-to-machine-learning.netlify.app/
 
 Repository on Github: https://github.com/compstat-lmu/lecture_i2ml
 

_pkgdown.yml

@@ -6,24 +6,7 @@ template:
   params:
     bootswatch: simplex
 
+
 navbar:
   title:
-  type: default
-  left:
-  - text: Content
-    href: articles/content.html
-  - text: Courses
-    menu:
-    - text: ML Summer School 2020
-      href: articles/summer_school_course.html 
-    - text: LMU Munich 2020 
-      href: articles/lmu_course.html 
-    - text: Uni Bielefeld 2020 
-      href: articles/ub_course.html 
-  - text: Team and License
-    href: articles/team.html
-  - text: References
-    href: articles/references.html
-  - text: Changelog
-    href: articles/changelog.html
-
+  type: default    

cheatsheets/CheatSheet_i2ml_1.tex

@@ -147,7 +147,7 @@
 						\hspace*{1ex}Discrete prediction for classification.
 						\\
 						\begin{codebox}
-							$\theta \in \Theta$ : model \textbf{parameters}
+							$\thetab = (\theta_1, \theta_2, ..., \theta_d) \in \Theta$ : model \textbf{parameters}
 						\end{codebox}
 						\hspace*{1ex}Some models may traditionally use different symbols.
 						\\

slides/R.mk

@@ -0,0 +1,7 @@
+FIGS = $(shell find . -maxdepth 1 -iname "fig-*.R" -printf "%f\n")
+PDFS = $(FIGS:%.R=../figure/%.pdf)
+
+all: $(PDFS) 
+
+$(PDFS): ../figure/%.pdf: %.R
+	Rscript $<

slides/evaluation/Makefile

@@ -1,27 +1 @@
-TSLIDES = $(shell find . -maxdepth 1 -iname "slides-*.tex")
-TPDFS = $(TSLIDES:%.tex=%.pdf)
-
-all: texclean $(TPDFS) 
-
-$(TPDFS): %.pdf: %.tex
-	pdflatex $<
-
-
-texclean: 
-	rm -rf *.out
-	rm -rf *.dvi
-	rm -rf *.log
-	rm -rf *.aux
-	rm -rf *.bbl
-	rm -rf *.blg
-	rm -rf *.ind
-	rm -rf *.idx
-	rm -rf *.ilg
-	rm -rf *.lof
-	rm -rf *.lot
-	rm -rf *.toc
-	rm -rf *.nav
-	rm -rf *.snm
-	rm -rf *.vrb
-	rm -rf *.synctex.gz
-	rm -rf *-concordance.tex
+include ../tex.mk

slides/evaluation/rsrc/Makefile

@@ -1,7 +1 @@
-FIGS = $(shell find . -maxdepth 1 -iname "fig-*.R" -printf "%f\n")
-PDFS = $(FIGS:%.R=../figure/%.pdf)
-
-all: $(PDFS) 
-
-$(PDFS): ../figure/%.pdf: %.R
-	Rscript $<
+include ../../R.mk

slides/forests/Makefile

@@ -1,27 +1 @@
-TSLIDES = $(shell find . -maxdepth 1 -iname "slides-*.tex")
-TPDFS = $(TSLIDES:%.tex=%.pdf)
-
-all: texclean $(TPDFS) 
-
-$(TPDFS): %.pdf: %.tex
-	pdflatex $<
-
-
-texclean: 
-	rm -rf *.out
-	rm -rf *.dvi
-	rm -rf *.log
-	rm -rf *.aux
-	rm -rf *.bbl
-	rm -rf *.blg
-	rm -rf *.ind
-	rm -rf *.idx
-	rm -rf *.ilg
-	rm -rf *.lof
-	rm -rf *.lot
-	rm -rf *.toc
-	rm -rf *.nav
-	rm -rf *.snm
-	rm -rf *.vrb
-	rm -rf *.synctex.gz
-	rm -rf *-concordance.tex
+include ../tex.mk

slides/forests/rsrc/Makefile

@@ -1,7 +1 @@
-FIGS = $(shell find . -maxdepth 1 -iname "fig-*.R" -printf "%f\n")
-PDFS = $(FIGS:%.R=../figure/%.pdf)
-
-all: $(PDFS) 
-
-$(PDFS): ../figure/%.pdf: %.R
-	Rscript $<
+include ../../R.mk

slides/ml-basics/Makefile

@@ -1,27 +1 @@
-TSLIDES = $(shell find . -maxdepth 1 -iname "slides-*.tex")
-TPDFS = $(TSLIDES:%.tex=%.pdf)
-
-all: texclean $(TPDFS) 
-
-$(TPDFS): %.pdf: %.tex
-	pdflatex $<
-
-
-texclean: 
-	rm -rf *.out
-	rm -rf *.dvi
-	rm -rf *.log
-	rm -rf *.aux
-	rm -rf *.bbl
-	rm -rf *.blg
-	rm -rf *.ind
-	rm -rf *.idx
-	rm -rf *.ilg
-	rm -rf *.lof
-	rm -rf *.lot
-	rm -rf *.toc
-	rm -rf *.nav
-	rm -rf *.snm
-	rm -rf *.vrb
-	rm -rf *.synctex.gz
-	rm -rf *-concordance.tex
+include ../tex.mk

slides/ml-basics/attic/basics-data-example-salary.tex

@@ -0,0 +1,168 @@
+\documentclass[11pt,compress,t,notes=noshow, xcolor=table]{beamer}
+\usepackage[]{graphicx}\usepackage[]{color}
+% maxwidth is the original width if it is less than linewidth
+% otherwise use linewidth (to make sure the graphics do not exceed the margin)
+\makeatletter
+\def\maxwidth{ %
+  \ifdim\Gin@nat@width>\linewidth
+    \linewidth
+  \else
+    \Gin@nat@width
+  \fi
+}
+\makeatother
+
+\definecolor{fgcolor}{rgb}{0.345, 0.345, 0.345}
+\newcommand{\hlnum}[1]{\textcolor[rgb]{0.686,0.059,0.569}{#1}}%
+\newcommand{\hlstr}[1]{\textcolor[rgb]{0.192,0.494,0.8}{#1}}%
+\newcommand{\hlcom}[1]{\textcolor[rgb]{0.678,0.584,0.686}{\textit{#1}}}%
+\newcommand{\hlopt}[1]{\textcolor[rgb]{0,0,0}{#1}}%
+\newcommand{\hlstd}[1]{\textcolor[rgb]{0.345,0.345,0.345}{#1}}%
+\newcommand{\hlkwa}[1]{\textcolor[rgb]{0.161,0.373,0.58}{\textbf{#1}}}%
+\newcommand{\hlkwb}[1]{\textcolor[rgb]{0.69,0.353,0.396}{#1}}%
+\newcommand{\hlkwc}[1]{\textcolor[rgb]{0.333,0.667,0.333}{#1}}%
+\newcommand{\hlkwd}[1]{\textcolor[rgb]{0.737,0.353,0.396}{\textbf{#1}}}%
+\let\hlipl\hlkwb
+
+\usepackage{framed}
+\makeatletter
+\newenvironment{kframe}{%
+ \def\at@end@of@kframe{}%
+ \ifinner\ifhmode%
+  \def\at@end@of@kframe{\end{minipage}}%
+  \begin{minipage}{\columnwidth}%
+ \fi\fi%
+ \def\FrameCommand##1{\hskip\@totalleftmargin \hskip-\fboxsep
+ \colorbox{shadecolor}{##1}\hskip-\fboxsep
+     % There is no \\@totalrightmargin, so:
+     \hskip-\linewidth \hskip-\@totalleftmargin \hskip\columnwidth}%
+ \MakeFramed {\advance\hsize-\width
+   \@totalleftmargin\z@ \linewidth\hsize
+   \@setminipage}}%
+ {\par\unskip\endMakeFramed%
+ \at@end@of@kframe}
+\makeatother
+
+\definecolor{shadecolor}{rgb}{.97, .97, .97}
+\definecolor{messagecolor}{rgb}{0, 0, 0}
+\definecolor{warningcolor}{rgb}{1, 0, 1}
+\definecolor{errorcolor}{rgb}{1, 0, 0}
+\newenvironment{knitrout}{}{} % an empty environment to be redefined in TeX
+
+\usepackage{alltt}
+\newcommand{\SweaveOpts}[1]{}  % do not interfere with LaTeX
+\newcommand{\SweaveInput}[1]{} % because they are not real TeX commands
+\newcommand{\Sexpr}[1]{}       % will only be parsed by R
+
+\usepackage[english]{babel}
+\usepackage[utf8]{inputenc}
+
+\usepackage{dsfont}
+\usepackage{verbatim}
+\usepackage{amsmath}
+\usepackage{amsfonts}
+\usepackage{bm}
+\usepackage{csquotes}
+\usepackage{multirow}
+\usepackage{longtable}
+\usepackage{booktabs}
+\usepackage{enumerate}
+\usepackage[absolute,overlay]{textpos}
+\usepackage{psfrag}
+\usepackage{algorithm}
+\usepackage{algpseudocode}
+\usepackage{eqnarray}
+\usepackage{arydshln}
+\usepackage{tabularx}
+\usepackage{placeins}
+\usepackage{tikz}
+\usepackage{setspace}
+\usepackage{colortbl}
+\usepackage{mathtools}
+\usepackage{wrapfig}
+\usepackage{bm}
+
+\usetikzlibrary{shapes,arrows,automata,positioning,calc,chains,trees, shadows}
+\tikzset{
+  %Define standard arrow tip
+  >=stealth',
+  %Define style for boxes
+  punkt/.style={
+    rectangle,
+    rounded corners,
+    draw=black, very thick,
+    text width=6.5em,
+    minimum height=2em,
+    text centered},
+  % Define arrow style
+  pil/.style={
+    ->,
+    thick,
+    shorten <=2pt,
+    shorten >=2pt,}
+}
+
+\usepackage{subfig}
+
+% Defines macros and environments
+\input{../../../style/common.tex}
+
+%\usetheme{lmu-lecture}
+\usepackage{../../../style/lmu-lecture}
+
+\let\code=\texttt
+\let\proglang=\textsf
+
+\setkeys{Gin}{width=0.9\textwidth}
+
+\title{Introduction to Machine Learning}
+% \author{Bernd Bischl, Christoph Molnar, Daniel Schalk, Fabian Scheipl}
+\institute{\href{https://compstat-lmu.github.io/lecture_i2ml/}{compstat-lmu.github.io/lecture\_i2ml}}
+\date{}
+
+\setbeamertemplate{frametitle}{\expandafter\uppercase\expandafter\insertframetitle}
+
+\begin{document}
+
+% Set style/preamble.Rnw as parent.
+
+% Load all R packages and set up knitr
+
+% This file loads R packages, configures knitr options and sets preamble.Rnw as 
+% parent file
+% IF YOU MODIFY THIS, PLZ ALSO MODIFY setup.Rmd ACCORDINGLY...
+
+% Defines macros and environments
+
+\input{../../../latex-math/basic-math.tex}
+\input{../../../latex-math/basic-ml.tex}
+
+\lecturechapter{Introduction: Data}
+\lecture{Introduction to Machine Learning}
+
+% ------------------------------------------------------------------------------
+
+\begin{vbframe}{Data in Machine Learning}
+
+\begin{itemize}
+
+  \item For instance, it is reasonable to assume a relationship between certain
+  features of a job-seeker, such as their field of expertise, academic 
+  qualifications and previous job experiences, and their salary.
+
+  \begin{center}
+    % FIGURE SOURCE: Screnshot from website (https://www.dice.com/salary-calculator)
+    \includegraphics[width = 0.7\textwidth]{../figure_man/salary_prediction.png}
+  \end{center}
+
+  \item In practical applications we frequently encounter high-dimensional data,
+  i.e., data with many features and/or observations.
+
+\end{itemize}
+
+\end{vbframe}
+
+% ------------------------------------------------------------------------------
+
+\endlecture
+\end{document}

slides/ml-basics/rsrc/Makefile

@@ -0,0 +1 @@
+include ../../R.mk