ComenzarEmpieza gratis

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.

Este ejercicio forma parte del curso

Feature Engineering for NLP in Python

Ver curso

Instrucciones del ejercicio

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

Ejercicio interactivo práctico

Prueba este ejercicio y completa el código de muestra.

# 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)
Editar y ejecutar código