Create vectorization.py

vectorization.py

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+from gensim.models import Word2Vec
+import pandas as pd
+
+
+spotify_data= pd.read_csv('spotify_data_processed.csv')
+
+
+
+
+# Asumiendo que spotify_data['cleaned_text'] contiene listas de palabras (tokens)
+spotify_data['cleaned_text'] = spotify_data['cleaned_text'].apply(eval)
+
+model = Word2Vec(sentences=spotify_data['cleaned_text'], vector_size=100, window=10, min_count=1, workers=5)
+# Guardar el modelo
+model.save("word2vec_model.model")