similarity

from gensim.models import Word2Vec

sentences = [
    ['customer', 'refund', 'payment', 'issue'],
    ['login', 'authentication', 'password', 'reset'],
    ['delivery', 'shipment', 'tracking', 'delay'],

Word embeddings with gensim for semantic similarity tasks

word-embeddings gensim nlp

by Dr. Elena Vasquez 1 tab

python

import numpy as np

embeddings = np.array([
    [0.9, 0.1, 0.2],
    [0.1, 0.8, 0.3],
    [0.7, 0.2, 0.4],

Linear algebra patterns for similarity and projection tasks

numpy linear-algebra embeddings

by Dr. Elena Vasquez 1 tab