Site update

README.md

@@ -5,79 +5,95 @@
 Status](https://travis-ci.org/ModelOriented/DALEXtra.svg?branch=master)](https://travis-ci.org/ModelOriented/DALEXtra)
 [![Coverage
 Status](https://img.shields.io/codecov/c/github/ModelOriented/DALEXtra/master.svg)](https://codecov.io/github/ModelOriented/DALEXtra?branch=master)
+[![CRAN\_Status\_Badge](http://www.r-pkg.org/badges/version/DALEXtra)](https://cran.r-project.org/package=DALEXtra)
 
-An extension for DALEX package
+## Overview
 
-# Anaconda
+The `DALEXtra` package is an extension pack for
+[DALEX](https://modeloriented.github.io/DALEX) package. This package
+provides easy to use connectors for models created with scikitlearn,
+keras, H2O, mljar and mlr.
 
-In order to be able to use some features associated with `DALEXtra`,
-Anaconda in needed. The easiest way to get it, is visting [Anconda
-website](https://www.anaconda.com/distribution). And choosing proper OS
-as it stands in the following picture.
-![](README_files/figure-gfm/anaconda1.png) There is no big difference
-bewtween Python versions when downloading conda therefore it is
-recommended to choose Python 3.7 (newer Anaconda version) and then
-downloading python 2.7.
+## Installation
 
-## Windows
-
-Crucial thing is adding conda to PATH environment variable when using
-Windows. You can do it during installation, by marking this checkbox.
+    # Install the development version from GitHub:
+
+    # it is recommended to install latest version of DALEX from GitHub
+    devtools::install_github("ModelOriented/DALEX")
+    # install.packages("devtools")
+    devtools::install_github("ModelOriented/DALEXtra")
 
-![](README_files/figure-gfm/anaconda2.png)
+Package `reticulate` will be downloaded along with `DALEXtra` but if you
+seek for it’s latests version it can be downloaded here
 
-or, if conda is already installed, by following [those
-instructions](https://stackoverflow.com/a/44597801/9717584).
+    devtools::install_github("rstudio/reticulate")
 
-## Unix
+Other packages useful with explanations.
 
-While using unixlike OS, adding conda to PATH is not required.
+    devtools::install_github("ModelOriented/ingredients")
+    devtools::install_github("ModelOriented/iBreakDown")
+    devtools::install_github("ModelOriented/shapper")
+    devtools::install_github("ModelOriented/auditor")
 
-# Installation and configuration
+Above packages can be used along with `explain` object to create
+explanations (ingredients, iBreakDown, shapper) or audit our model
+(audiotr).
 
-Package can be installed with execution of the following code
+## How to setup Anaconda
 
-    install.packages("devtools")
-    devtools::install_github("ModelOriented/DALEXtra")
-    devtools::install_github("ModelOriented/DALEX")
+In order to be able to use some features associated with `DALEXtra`,
+Anaconda in needed. The easiest way to get it, is visting [Anconda
+website](https://www.anaconda.com/distribution). And choosing proper OS
+as it stands in the following picture.
+![](https://raw.githubusercontent.com/ModelOriented/DALEXtra/master/README_files/figure-gfm/anaconda1.png)
+There is no big difference bewtween Python versions when downloading
+Anaconda. You can always create virtual environment with any version of
+Pytho no matter which version was downloaded first.
 
-It is recommended to install latests github version of DALEX
+### Windows
 
-Package `reticulate` will be downloaded along with `DALEXtra` but if you
-seek for its latests version it can be downloaded here
+Crucial thing is adding conda to PATH environment variable when using
+Windows. You can do it during installation, by marking this
+checkbox.
 
-    devtools::install_github("rstudio/reticulate")
+![](https://raw.githubusercontent.com/ModelOriented/DALEXtra/master/README_files/figure-gfm/anaconda2.png)
 
-Packages useful with explanations
+or, if conda is already installed, by following [those
+instructions](https://stackoverflow.com/a/44597801/9717584).
 
-    devtools::install_github("ModelOriented/ingredients")
-    devtools::install_github("ModelOriented/iBreakDown")
-    devtools::install_github("ModelOriented/shapper")
-    devtools::install_github("ModelOriented/auditor")
+### Unix
 
-<https://modeloriented.github.io/DALEXtra/>
+While using unixlike OS, adding conda to PATH is not required.
 
-# Demo
+## Demo
 
 Here we will present short use case for our package and its
 compatibility with Python
 
-## Loading data
+### Loading data
 
-First we need data, explainer is useless without them. Thing is Python
-object does not store training data so always have to proviede dataset.
-Feel free to use those attached to `DALEX` package or those stored in
-`DALEXtra`
+First we need provide the data, explainer is useless without them. Thing
+is Python object does not store training data so always have to provide
+dataset. Feel free to use those attached to `DALEX` package or those
+stored in `DALEXtra`
 files.
 
 ``` r
 titanic_test <- read.csv(system.file("extdata", "titanic_test.csv", package = "DALEXtra"))
 ```
 
-Keep in mind that that dataframe includes targer variable (18th column)
-and scikit-learn models do not like it
+Keep in mind that dataframe includes target variable (18th column) and
+scikit-learn models cannot work with it.
 
-## Creating explainer
+### Creating explainer
+
+Creating exlainer from scikit-learn Python model is very simple thanks
+to `DALEXtra`. The only thing you need to provide is path to pickle and,
+if necessery, something that lets recognize Python environment. It may
+be .yml file with packages specification, name of existing conda
+environment or path to Python virtual environment. Execution of
+`scikitlearn_explain` only with .pkl file and data will cause usage of
+default Python.
 
 ``` r
 library(DALEXtra)
@@ -96,18 +112,11 @@ data = titanic_test[,1:17], y = titanic_test$survived)
     ##   -> residuals         :  numerical, min =  -0.8669431 , mean =  0.02248468 , max =  0.9791387  
     ## A new explainer has been created!
 
-Creating exlainer from scikit-learn Python model is very simple thanks
-to `DALEXtra`. The only thing you need to provide is path to pickle and,
-if necessery, something that lets recognize Python environment. It may
-be .yml file with packages specification, name of existing conda
-environment or path to Python virtual environment. Execution of
-`scikitlearn_explain` only with .pkl file and data will cause usage of
-default Python.
-
-## Creating explanations
+### Creating explanations
 
-Now with explainer ready we can use any of DrWhy.ai universe tools to
-make explanations. Here is a small demo
+Now with explainer ready we can use any of
+[DrWhy.ai](https://github.com/ModelOriented/DrWhy/blob/master/README.md)
+universe tools to make explanations. Here is a small demo.
 
 ``` r
 library(DALEX)
@@ -170,3 +179,8 @@ predict(explainer, titanic_test[1:10, 1:17])
 
     ##  [1] 0.3565896 0.1321947 0.7638813 0.1037486 0.1265221 0.2949228 0.1421281
     ##  [8] 0.1421281 0.4154695 0.1321947
+
+## Acknowledgments
+
+Work on this package was financially supported by the ‘NCN Opus grant
+2016/21/B/ST6/02176’.

_pkgdown.yml

@@ -1,10 +1,6 @@
 template:
   package: DrWhyTemplate
   default_assets: false
-home:
-  links:
-  - text: Source code
-    href: https://github.com/ModelOriented/DALEXtra
 
 reference:
   - title: Explainers