TF-IDF

# Import TfidfModel
from gensim.models.tfidfmodel import TfidfModel

# Create a new TfidfModel using the corpus: tfidf
tfidf = TfidfModel(corpus)

# Calculate the tfidf weights of doc: tfidf_weights
tfidf_weights = tfidf[corpus[0]]

# Print the first five weights
print(tfidf_weights[:5])

# Sort the weights from highest to lowest: sorted_tfidf_weights
sorted_tfidf_weights = sorted(tfidf_weights, key=lambda w: w[1], reverse=True)

# Print the top 5 weighted words
for term_id, weight in sorted_tfidf_weights[:5]:
    print(dictionary.get(term_id), weight)