Challenge: Creating a Bag of Words

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Your task is to display the vector for the 'graphic design' bigram in a BoW model:

Import the CountVectorizer class to create a BoW model.
Instantiate the CountVectorizer class as count_vectorizer, configuring it for a frequency-based model that includes both unigrams and bigrams.
Utilize the appropriate method of count_vectorizer to generate a BoW matrix from the 'Document' column in the corpus.
Convert bow_matrix to a dense array and create a DataFrame from it, setting the unique features (unigrams and bigrams) as its columns. Assign this to the variable bow_df.
Display the vector for 'graphic design' as an array, rather than as a pandas Series.

Перейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантів

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Секція 3. Розділ 5

Завдання

Swipe to show code editor

Your task is to display the vector for the 'graphic design' bigram in a BoW model:

Import the CountVectorizer class to create a BoW model.
Instantiate the CountVectorizer class as count_vectorizer, configuring it for a frequency-based model that includes both unigrams and bigrams.
Utilize the appropriate method of count_vectorizer to generate a BoW matrix from the 'Document' column in the corpus.
Convert bow_matrix to a dense array and create a DataFrame from it, setting the unique features (unigrams and bigrams) as its columns. Assign this to the variable bow_df.
Display the vector for 'graphic design' as an array, rather than as a pandas Series.

Все було зрозуміло?

Дякуємо за ваш відгук!

Секція 3. Розділ 5

Завдання

Swipe to show code editor

Your task is to display the vector for the 'graphic design' bigram in a BoW model:

Import the CountVectorizer class to create a BoW model.
Instantiate the CountVectorizer class as count_vectorizer, configuring it for a frequency-based model that includes both unigrams and bigrams.
Utilize the appropriate method of count_vectorizer to generate a BoW matrix from the 'Document' column in the corpus.
Convert bow_matrix to a dense array and create a DataFrame from it, setting the unique features (unigrams and bigrams) as its columns. Assign this to the variable bow_df.
Display the vector for 'graphic design' as an array, rather than as a pandas Series.

Все було зрозуміло?

Дякуємо за ваш відгук!

Завдання

Swipe to show code editor

Your task is to display the vector for the 'graphic design' bigram in a BoW model:

Import the CountVectorizer class to create a BoW model.
Instantiate the CountVectorizer class as count_vectorizer, configuring it for a frequency-based model that includes both unigrams and bigrams.
Utilize the appropriate method of count_vectorizer to generate a BoW matrix from the 'Document' column in the corpus.
Convert bow_matrix to a dense array and create a DataFrame from it, setting the unique features (unigrams and bigrams) as its columns. Assign this to the variable bow_df.
Display the vector for 'graphic design' as an array, rather than as a pandas Series.

Секція 3. Розділ 5