Python, NLP, Numpy, Scikit Learn.
word_tokenize(corpus.raw('sent1.txt'))] vec1 = encoder.word_vector(sent1) print(vec1) # [ 0.01989746 0.24707031 -0.23632812 ... -0.24707031 0.05249023 # 0.19824219] print(vec1.shape) # (3000,) sent2 = [word for word in word_tokenize(corpus.raw('sent2.txt'))] vec2 = encoder.word_vector(sent2)