R

How Easy Is It to Understand What Donald Trump Says?

Aside from their political differences, Donald Trump and Barack Obama have very contrasting personalities, traits and characters. Obama is known to be a great communicator and an articulate speaker whose speeches are used in English classes to show how one should speak proper English. On the other hand, Trump is not the most eloquent English speaker or US president in history. Every now and then, you can find a clip on the web where Donald Trump is being mocked for the way he speaks or mispronounces words.

R Packages

Delgosha Delgosha is an opinionated package which aims to provide a collection of ggplot2 themes for RTL languages (mostly Persian). img 1https://github.com/mcnakhaee/delgosha/blob/master/README_files/figure-gfm/unnamed-chunk-3-1.pnghttps://github.com/mcnakhaee/delgosha/blob/master/README_files/figure-gfm/unnamed-chunk-3-1.png)[] ### Dadegan Dadegan is a simple package which contains a handful of useful Persian datasets.

Which Presidential Debate Was More Chaotic?

Many people watched the first Presidential Debate between Biden and Trump and thought that this debate was chaotic, full of vulgar language, interruptions, and in a word, really ugly! Some people even consider this debate as the worst debate in the modern history of US Presidential Elections! Four years ago, Trump was also a presidential candidate and ran against Hillary Clinton. The Presidential Debates in 2016 were not exceptionally friendly or civilized.

Explaining Machine Learning Models Using Contextual Importance and Contextual Utility

Introduction What Kinds of explanation does CIU generate? How does CIU work? A toy example: predicting breast Permutation feature importance Decision Tree Classifier Random Forest Classifier Gradient Boosting Classifier Explaining a single observation Generating Textual Explanations Drawbacks Introduction Explainability is a hot topic in the machine learning research community these days. Over the past few years, many methods have been introduced to understand how a machine learning model makes a prediction.

The Happiest, Saddest, Most Energetic and Most Popular Persian Singers on Spotify

Introduction I am a music lover, and like my other hobbies, I am really interested in applying data science methods to it. A few months ago, I participated in the third week of the TidyTuesday project, where I made a map of Spotify songs based on audio features and a dimensionality reduction algorithm called UMAP. Since then, I have been using Spotify’s Web API to collect data, and recently, I decided to look at some of my favorite Iranian artists and their songs on Spotify.

Analyzing the 2020 Democratic Presidential Debates - Part 2

1. Introduction Many of us could not watch every 2020 Democratic Primary debate. It was important for some of us to know what happened during the debates. In my case, I was reading about what happened in debates in some online newspapers, or I watched a highlight of a debate on Youtube the next day. However, they only give a summary of a debate or just broadcast a portion of debates that includes a heated exchange of opinions between candidates.

Analyzing the 2020 Democratic Party Presidential Debates - Part 1

I am not a US citizen, nor have I been to the United States, but that does not mean that I should not care about the result of the US presidential election. The outcome of the election plays an important role in my life and almost everyone’s else around the world. So, I have been following the US politics for a few years. I consider everything and every issue around me as a data science problem and an opportunity to use data science.

Going Back to the Roots! How Much Influence Did Arabic Have on Persian Literature?

Since the conquest of Persia (now Iran) by the Muslim forces in the 7th century, Arabic culture and language have had an enormous influence on Iran and Iranians. Although Iran had never fully adapted Arabic as its primary language, the new Persian (Farsi) language is a mix of Arabic and the old Persian (Pahlavi) and almost uses the same alphabet for writing. Also, in some parts of Iran, Arabic is the daily-life language.

The Map of Spotify Songs

In the 4th week of the Tidy Tuesday project, a very interesting and fun dataset was proposed to the data science community. The dataset contains information about thousands of songs on Spotify’s platform and along with their metadata and audio features. You can download the dataset can using the following piece of code. 4th week of the Tidy Tuesday project spotify_songs <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-01-21/spotify_songs.csv') head(spotify_songs) ## # A tibble: 6 x 23 ## track_id track_name track_artist track_popularity track_album_id ## <chr> <chr> <chr> <dbl> <chr> ## 1 6f807x0~ I Don't C~ Ed Sheeran 66 2oCs0DGTsRO98~ ## 2 0r7CVbZ~ Memories ~ Maroon 5 67 63rPSO264uRjW~ ## 3 1z1Hg7V~ All the T~ Zara Larsson 70 1HoSmj2eLcsrR~ ## 4 75Fpbth~ Call You ~ The Chainsm~ 60 1nqYsOef1yKKu~ ## 5 1e8PAfc~ Someone Y~ Lewis Capal~ 69 7m7vv9wlQ4i0L~ ## 6 7fvUMiy~ Beautiful~ Ed Sheeran 67 2yiy9cd2QktrN~ ## # .