This project analyzes a Netflix dataset of TV shows and movies using unsupervised learning and statistical methods in R. It includes basic data analysis, outlier detection, and clustering to uncover patterns in ratings, genres, actors, and temporal trends.
This work was completed as part of the lecture Unsupervised Learning and Evolutionary Optimisation Using R (ULEOUR) offered during the Winter Semester 2024/25 at Paderborn University.
Requires R with packages for data analysis, visualization, and clustering.
Run the provided R scripts to reproduce the analysis and visualizations.
Provides valuable insights into audience preferences, genre impacts, and industry trends.
Abhipsa Roy
Allen Mundackal
Namit Joshi
Pranjal Parmar
Saurabh Palve
Tanmay Mhatre
University of Paderborn, Germany