Notice: This page requires JavaScript to function properly.
Please enable JavaScript in your browser settings or update your browser.Oppiskele Challenge: Creating a Bag of Words | Basic Text Models
Introduction to NLP

bookChallenge: Creating a Bag of Words

Tehtävä

Swipe to start coding

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

  1. Import the CountVectorizer class to create a BoW model.

  2. Instantiate the CountVectorizer class as count_vectorizer, configuring it for a frequency-based model that includes both unigrams and bigrams.

  3. Utilize the appropriate method of count_vectorizer to generate a BoW matrix from the 'Document' column in the corpus.

  4. 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.

  5. Display the vector for 'graphic design' as an array, rather than as a pandas Series.

Ratkaisu

Switch to desktopVaihda työpöytään todellista harjoitusta vartenJatka siitä, missä olet käyttämällä jotakin alla olevista vaihtoehdoista
Oliko kaikki selvää?

Miten voimme parantaa sitä?

Kiitos palautteestasi!

Osio 3. Luku 5
single

single

Kysy tekoälyä

expand

Kysy tekoälyä

ChatGPT

Kysy mitä tahansa tai kokeile jotakin ehdotetuista kysymyksistä aloittaaksesi keskustelumme

close

Awesome!

Completion rate improved to 4.17

bookChallenge: Creating a Bag of Words

Tehtävä

Swipe to start coding

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

  1. Import the CountVectorizer class to create a BoW model.

  2. Instantiate the CountVectorizer class as count_vectorizer, configuring it for a frequency-based model that includes both unigrams and bigrams.

  3. Utilize the appropriate method of count_vectorizer to generate a BoW matrix from the 'Document' column in the corpus.

  4. 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.

  5. Display the vector for 'graphic design' as an array, rather than as a pandas Series.

Ratkaisu

Switch to desktopVaihda työpöytään todellista harjoitusta vartenJatka siitä, missä olet käyttämällä jotakin alla olevista vaihtoehdoista
Oliko kaikki selvää?

Miten voimme parantaa sitä?

Kiitos palautteestasi!

Osio 3. Luku 5
single

single

close

Awesome!

Completion rate improved to 4.17

bookChallenge: Creating a Bag of Words

Pyyhkäise näyttääksesi valikon

Tehtävä

Swipe to start coding

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

  1. Import the CountVectorizer class to create a BoW model.

  2. Instantiate the CountVectorizer class as count_vectorizer, configuring it for a frequency-based model that includes both unigrams and bigrams.

  3. Utilize the appropriate method of count_vectorizer to generate a BoW matrix from the 'Document' column in the corpus.

  4. 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.

  5. Display the vector for 'graphic design' as an array, rather than as a pandas Series.

Ratkaisu

Switch to desktopVaihda työpöytään todellista harjoitusta vartenJatka siitä, missä olet käyttämällä jotakin alla olevista vaihtoehdoista
Oliko kaikki selvää?

Miten voimme parantaa sitä?

Kiitos palautteestasi!

some-alt