This analysis was featured on: The Hustle newsletter (lead story), TechCrunch, Hacker News, The Growth Newsletter (issue #021), Social Blade, Data Science Weekly newsletter (Jul 09 2020's issue), Weekly, Tubefilter, Younes Talk, and more. Around 1.5 years ago, I did an analysis of YouTube...
In this post, I will present the results of a thorough analysis of international football matches that took place between 1872 and 2018 (147 years). International matches means matches between national teams like Brazil, Italy, Japan, Egypt, etc. The analysis uses a dataset published on Kaggle on...
Introduction In this post, I will talk about a project I’ve done in order to get IBM Data Science Professional Certificate. In this project, the neighborhoods of two important cities in the world—New York City (NYC) and Toronto—were clustered into groups of similar items. One can use the results...
In this document, I will briefly explain my way of solving the VSB Power Line Fault Detection competition. The metric used in that competition was Matthews correlation coefficient (MCC) between the predicted and the observed response. My final score was 0.58655; the best score was 0.71899 (a...
I had a course named "Data Analytics" in the previous semester of my study at University of Malaya. We were required to do a project in this course that involves the main steps in the data-science process including data cleaning and preparation, data exploration, predictive modeling,...
YouTube is the most popular and most used video platfrom in the world today. YouTube has a list of trending videos that is updated constantly. Here we will use Python with some packages like Pandas and Matplotlib to analyze a dataset that was collected over 205 days. For each of...