video_vector_generator.py
432 Bytes
import pandas as pd
from gensim.models import Word2Vec
def vectorization_video():
print('[0.1 0.2]')
if __name__ == '__main__':
tag_vectors = Word2Vec.load("esot3ria/tags_word2vec.model").wv
video_vectors = Word2Vec().wv # Empty model
# Load video recommendation tags.
video_tags = pd.read_csv('esot3ria/video_recommendation_tags.csv')
for i, row in video_tags.iterrows():
video_id = row[0]