Music significantly influences human emotions and health. Studies have shown its impact on improving mood and reducing pain and anxiety. Recent research has focused on analyzing songs to understand the factors behind their popularity. This involves examining song samples, recording their features, and using this data to predict song popularity.
The dataset used for this project is sourced from Kaggle.
- Review and clean the dataset to ensure it is ready for analysis.
- Identify and address any missing or inconsistent data.
- Develop regression models to predict song popularity.
- Select relevant features, experiment with various regression techniques, and refine the models to enhance prediction accuracy.
- Evaluate the performance of each model using metrics like R-squared (R2) and Root Mean Square Error (RMSE).
- Compare the models to determine which performs best in predicting song popularity.
The aim is to understand and quantify the factors that contribute to a song's success.