Project Summery

The Spotify Persian Music Analyzer is a Jupyter notebook that offers a robust toolset for exploring and understanding Persian music tracks available on Spotify. The main stages of this project include data preprocessing, visualizing key patterns, and genre classification.

Before delving into analysis and classification, the data undergoes rigorous preprocessing. This step involves handling missing values, data normalization, and feature engineering to ensure the dataset is clean and ready for analysis. Properly preprocessed data sets the foundation for accurate insights.

One of the primary objectives of this project is genre classification. Leveraging machine learning algorithms, we create models to predict the genre labels of Persian music tracks based on their acoustic properties and metadata. The classification results help us identify distinctive characteristics of different music genres within the dataset.

Finally, by using Random Forest model, we managed to find the best accuracy among all other models.