Comparing linear_kernel and cosine_similarity
In this exercise, you have been given tfidf_matrix which contains the tf-idf vectors of a thousand documents. Your task is to generate the cosine similarity matrix for these vectors first using cosine_similarity and then, using linear_kernel.
We will then compare the computation times for both functions.
This exercise is part of the course
Feature Engineering for NLP in Python
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Record start time
start = time.time()
# Compute cosine similarity matrix
cosine_sim = ____(____, ____)
# Print cosine similarity matrix
print(cosine_sim)
# Print time taken
print("Time taken: %s seconds" %(time.time() - start))