The Spotify Hit Predictor project aims to leverage machine learning techniques to predict the success of a song based on specific metrics such as loudness and tone. This project was a collaborative effort where various machine learning models were implemented and evaluated.
- Utilized Logistic Regression and Random Forest models to predict hit songs.
- Achieved an accuracy of 98% with the Logistic Regression model.
- Analyzed song features and metrics to determine their impact on a song's success.
- Python
- Pandas
- Scikit-Learn
- Logistic Regression
- Random Forest