In this study, general information about usage areas, methods and importance of DL and ML in music industry. The study offers an academic perspective on DL in music industry and serves as shining light upon how fast AI, DL and ML develops and how much they are becoming a part of our daily life. It is aimed to give the reader an idea about the use of DL on music by providing information about the definition of music genres, DL algorithms, the dataset of study and different uses of DL and ML methods with music. It is tried to explain that how much DL and ML effects our life and how they are already in use.
In the study, sound features were extracted with the help of Python libraries, dominant features were determined using feature selection methods and the performances of classification algorithms were compared. Different attributes were selected from the articles and studies that were similar to the study and it was aimed to compare the algorithm results they obtained with the algorithm results of this study.
Keywords: Music genre classification, music information retrieval, deep learning, machine learning, classification algorithms, feature extraction, feature importance, PCA.
- **Ege DURMAZ
- **Eyüp Furkan ÖZMEN