-
Notifications
You must be signed in to change notification settings - Fork 29
/
README.Rmd
55 lines (30 loc) · 2.57 KB
/
README.Rmd
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
```{r setup, echo = FALSE}
knitr::opts_chunk$set(
fig.path = "man/figures/README-",
out.width = "200px"
)
```
[](https://cran.r-project.org/package=funModeling)
[](https://cran.r-project.org/package=funModeling)
# Hello!
This package contains a set of functions related to exploratory data analysis, data preparation, and model performance. It is used by people coming from business, research, and teaching (professors and students).
<img src="https://datascienceheroes.com/img/blog/funModeling_cover.png" alt="funModeling" width="400px"/>
<img src="https://s3.amazonaws.com/datascienceheroes.com/img/blog/funModeling_logo_hq.png" alt="funModeling" width="300px"/>
## Books
`funModeling` is intimately related to the _Data Science Live Book_ -Open Source- (2017) in the sense that most of its functionality is used to explain different topics addressed by the book.
<img src="https://livebook.datascienceheroes.com/introduction/data-science-live-book.png" alt="Data Science Live Book" width="300px"/>
Versions:
* EN: [Data Science Live Book](https://livebook.datascienceheroes.com/)
* ES: [Libro Vivo de Ciencia de Datos](https://librovivodecienciadedatos.ai)
In the _Download_ section, you can buy (name your price) a digital copy of the book in PDF, mobi and pub.
## Blog posts based on `funModeling`:
* [Exploratory Data Analysis in R (introduction)](https://blog.datascienceheroes.com/exploratory-data-analysis-in-r-intro/)
* [Automatic data types checking in predictive models](https://blog.datascienceheroes.com/automatic-data-types-checking-in-predictive-models/)
* [Fast data exploration for predictive modeling](https://blog.datascienceheroes.com/fast-data-exploration-for-predictive-modeling/)
* [New discretization method: Recursive information gain ratio maximization](https://blog.datascienceheroes.com/discretization-recursive-gain-ratio-maximization/)
## Official page
* [funModeling official webpage](http://pablo14.github.io/funModeling/)
* Check the vignette [here](http://pablo14.github.io/funModeling/articles/funModeling_quickstart.html).
## If you speak Spanish...
<img src="https://s3.amazonaws.com/datascienceheroes.com/img/blog/Logo_Datos_Vivos.png" alt="Escuela de Datos Vivos" width="250px"/>
You are invited to the [Escuela de Datos Vivos](https://escueladedatosvivos.ai/), a data school founded by the same funModeling / DSLB author. There you can find free and paid courses, blog post, youtube channel, using R and Python.