espositic / playlist_recommender-ICON

Implementazione di un sistema di raccomandazione di playlist musicali basato su K-Means Clustering, e di algoritmi quali Random Forest, K-Nearest Neighbors, Decision Tree e Regressione Logistica per la predizione della popolaritá di una canzone.

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decision-tree-classifier k-means-clustering knn-classifier logistic-regression playlist-generator python random-forest-classifier spotify-dataset

playlist_recommender-ICON

Repository per il caso di studio di Ingegneria della Conoscenza A.A. 2021-2022 - Università degli Studi di Bari Aldo Moro.

Studenti

Esposito Matteo - 718240
Giuseppe Galgano - 717510

Clonare il progetto

git clone https://github.com/espositic/playlist_recommender-ICON.git

Creare l'ambiente virtuale

cd playlist_recommender-ICON.git

python -m venv playlist_recommender-ICON

Installare le dipendenze:

pip install -r requirements.txt

Esecuzione

cd code

python main.py

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decision-tree-classifier k-means-clustering knn-classifier logistic-regression playlist-generator python random-forest-classifier spotify-dataset

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