🎵 Music Recommendation System

This repository hosts a collection of machine learning models designed to recommend songs by predicting whether a user is likely to "like" a track based on its audio features.

📁 Files Included

data.csv — Dataset of 195 songs with features like danceability, energy, loudness, tempo, etc.
Trained model files:
- logistic_regression.joblib
- random_forest.joblib
- xgboost.joblib
- svm.joblib
- voting_classifier.joblib
- catboost_model.cbm
- ann_model.keras
final_model_card_scaled.pdf — Full model evaluation, comparison table, and chart

🧠 Models Used

Logistic Regression
Random Forest
XGBoost
Support Vector Machine (SVM)
Voting Classifier (Ensemble)
CatBoost
Artificial Neural Network (ANN)

📊 Evaluation

All models were evaluated using:

Accuracy
Precision
Recall
F1-Score

Refer to the PDF final_model_card_scaled.pdf for full details.

📬 Contact

Maintained by Sujal Thakkar.