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tf-idf vectors for TED talks

In this exercise, you have been given a corpus ted which contains the transcripts of 500 TED Talks. Your task is to generate the tf-idf vectors for these talks.

In a later lesson, we will use these vectors to generate recommendations of similar talks based on the transcript.

This exercise is part of the course

Feature Engineering for NLP in Python

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Exercise instructions

  • Import TfidfVectorizer from sklearn.
  • Create a TfidfVectorizer object. Name it vectorizer.
  • Generate tfidf_matrix for ted using the fit_transform() method.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Import TfidfVectorizer
from ____ import ____

# Create TfidfVectorizer object
____

# Generate matrix of word vectors
tfidf_matrix = vectorizer.____(____)

# Print the shape of tfidf_matrix
print(tfidf_matrix.shape)
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