Music Recommendation systems

This project develops a music recommendation system based on user listening habits. Exploratory data analysis and data cleaning are performed on the dataset. The model is built using LightGBM and logistic regression algorithms. The accuracy of the model on test data is evaluated. The project showcases the effectiveness of the recommendation system in providing personalized music suggestions.