Project Overview
This is an Exploratory Data Analysis project regarding the popularity of songs derived from the last seven decades (1950 - 2010), with various regression and classification machine learning problems.
The original source of the data comes from this kaggle repository. Consequently, this data was modified (e.g. merging the CSV files provided) in such a way for the construction of a class competition at Strathclyde University in the module of Machine Learning (academic year 2019-20), leading to two problems: a regression and a classification problem.
The aim was the identification of the most important attributes that the most popular songs share and have in common. In the regression problem, various models were built in order to predict the popularity of the songs, whereas the classification problem led to the construction of models that predicted their music genre.