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Steam Games at PySpark Scale

Big Data Processing · University of Oulu · Mar - May 2025

97,405 games · 69% variance · Random Forest

A Big Data Processing course project at the University of Oulu, on a 97,405-game Steam dataset.

I analyzed the dataset with Apache Spark and PySpark: exploratory analysis followed by modeling with Random Forest and Linear Regression, identifying success factors such as engagement, recency, and indie/action genres. The Random Forest Regressor reached 69% variance explanation.