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.
Cet exercice fait partie du cours
Feature Engineering for NLP in Python
Exercice interactif pratique
Essayez cet exercice en complétant cet exemple de 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))