---
title: "Getting Started"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Getting Started}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```

## Learning

Overview of available machine learning frameworks in R, which are ordered from 
**cutting-edge** to **outdated**:

1. [tidymodels](https://tidymodels.org): collection of packages for modeling and
machine learning using [tidyverse](https://tidyverse.org) principle covering the 
whole workflow (data pre-processing to evaluating model performance). Should also 
make it simple to switch to between different models. Recommended e-learning 
course (~4h) is offered by DataCamp [Modeling with tidymodels in R](https://learn.datacamp.com/courses/modeling-with-tidymodels-in-r). 

2. [mlr3](https://mlr3.mlr-org.com/): R package developed by statisticians at 
TU Dortmund. Should make it easy to develop different machine learning models. 
*Maybe an alternative to [tidymodels](https://tidymodels.org) approach?*

3. [caret](https://topepo.github.io/caret/index.html): R package for machine learning. *Outdated, as main developer Max Kuhn now works for R Studio for improving the [tidymodels](https://tidymodels.org) framework mentioned above.*

## Resources

**Books** 

* [Max Kuhn & Julia Silge (2021): Tidy Modeling with R](https://www.tmwr.org/) (free HTML version)

* [Becker et al. 2021: mlr3 book](https://mlr3book.mlr-org.com/) (free HTML version)

* [Chester Ismay & Albert Y. Kim (2021): Statistical Inference via Data Science - A ModernDive into R and the Tidyverse](https://moderndive.com/) (free HTML version)

* [Bradley Boehmke & Brandon Greenwell (2020): Hands-On Machine Learning with R](https://bradleyboehmke.github.io/HOML/) (free HTML version)

* [Hefin Ioan Rhys (2020): Machine Learning with R, the tidyverse, and mlr](https://livebook.manning.com/book/machine-learning-for-mortals-mere-and-otherwise/chapter-1/v-4/) (partly free HTML version)

***General Book Recommendation for ...***

> "... R users who want to improve their programming skills and understanding of 
the language. It should also be useful for programmers coming to R from other 
languages, "
>
> --- [Hadley Wickam (2021): Advanced R (2nd edition)](https://adv-r.hadley.nz/) (free HTML version)

**E-Learning plattform Datacamp**: offers more than [37 Machine Learning courses in R](https://learn.datacamp.com/search?utf8=%E2%9C%93&q=machine+learning&tab=courses&facets%5Btechnology%5D%5B%5D=R). At KWB we have a premium company account. If you are 
working for KWB and interested please follow the [Learning R on DataCamp](https://kwb-r.github.io/fakin.doc/faq.html#learning-r-on-datacamp) 
workflow.
