https://github.com/ilijamihajlovic/random-forest-classification
This project demonstrates how to build a Random Forest Classifier to predict music genres using audio feature data from Spotify. The model is trained on a curated subset of the spotify_tracks.csv dataset, focusing on popular genres such as pop, country, hip-hop, rock, latin, edm and more.
https://github.com/ilijamihajlovic/random-forest-classification
ai artificial-intelligence machine-learning machine-learning-algorithms machinelearning pandas python random-forest random-forest-classifier sckiit-learn sckit-learn
Last synced: 4 months ago
JSON representation
This project demonstrates how to build a Random Forest Classifier to predict music genres using audio feature data from Spotify. The model is trained on a curated subset of the spotify_tracks.csv dataset, focusing on popular genres such as pop, country, hip-hop, rock, latin, edm and more.
- Host: GitHub
- URL: https://github.com/ilijamihajlovic/random-forest-classification
- Owner: IlijaMihajlovic
- Created: 2025-06-11T12:57:33.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2025-06-11T14:33:19.000Z (4 months ago)
- Last Synced: 2025-06-11T16:08:28.672Z (4 months ago)
- Topics: ai, artificial-intelligence, machine-learning, machine-learning-algorithms, machinelearning, pandas, python, random-forest, random-forest-classifier, sckiit-learn, sckit-learn
- Language: Jupyter Notebook
- Homepage:
- Size: 7.96 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md