Netflix

This project leverages the R programming language to delve into Netflix's content strategy through data analysis. By examining movie types, categories, and descriptions, we categorize content into genres and themes, using charts and graphs to visually map genre prevalence and trends.

World University Rankings

Utilized R programming to conduct a comprehensive analysis of the factors influencing university rankings. The project aimed to identify key determinants impacting overall scores, examine the contribution of various variables to institutional rankings, and explore trends such as regional disparities

Football Stats Hub

The Football Stats Hub is a database system designed to manage and analyze extensive NFL data, bridging the gap between raw data and actionable insights. The system supports sports analysts, fantasy football players, and industry professionals by providing real-time, queryable statistics and predict

NBA Playoff Predictions (2010-2022)

Built a binary classification model to predict NBA playoff qualification using team-level season statistics from 2010 to 2022. Performed data wrangling, exploratory data analysis (EDA), feature engineering, and model development using logistic regression, random forest, and XGBoost. Evaluated models