Posts

Explaining Machine Learning Models Using Contextual Importance and Contextual Utility

A machine learning explanability algorithm

Covid-19 Trends in the Netherlands

R
Data Visualizaion
Covid-19

Based on data published by RIVM in this post, I looked at how Covid-19 cases spread throughout the Netherlands.

How Easy Is It to Understand What Donald Trump Says?

The computational complexity of the language that Trump uses in his speeches

Which Presidential Debate Was More Chaotic?

R
NLP

In this post, I looked at how Biden and Trump interrupted each other during the first Presidential debate and compared it with the recent Presidential debates.

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

R
Visualization

I investigate the difference between audio features of Iranian songs and singers on Spotify.

Analyzing the 2020 Democratic Presidential Debates - Part 2

NLP
R
Election
Spacy

A short description of the post.

The Map of Spotify Songs

R
Machine Learning
Dimensionaliy Reduction

Mapping high dimensional audio features from Spotify's into a 2D space using UMPAN and TSNE algorithms.

Explainable Data Science Summer School

XAI - Data Science

A short description of the post.

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Text and figures are licensed under Creative Commons Attribution CC BY-SA 4.0. Source code is available at https://github.com/mcnakhaee, unless otherwise noted. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".