Python, NLP, Numpy, Scikit Learn.
print(vec2) # [-0.11767578 -0.13769531 -0.140625 ... -0.03295898 -0.01733398 # 0.13476562] print(vec2.shape) # (4500,) As you can see, the vectors are 3000 and 4500 values for just two sentences. The result is document-specific matrix where each column represents the documents token appearing as