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Data Preprocessing

bookChallenge 2

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So, now let's remember what we do with text data. You will be working with the 'reviews.csv' dataset, and your task will be to encode text data using the bag of words method.

  1. Create a CountVectorizer object to tokenize text
  2. Fit data to the tokenizer
  3. Print the vocabulary of the tokenizer
  4. Encode 'Text' column
  5. Print the results

Løsning

Switch to desktopSkift til skrivebord for at øve i den virkelige verdenFortsæt der, hvor du er, med en af nedenstående muligheder
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Sektion 6. Kapitel 2
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bookChallenge 2

Opgave

Swipe to start coding

So, now let's remember what we do with text data. You will be working with the 'reviews.csv' dataset, and your task will be to encode text data using the bag of words method.

  1. Create a CountVectorizer object to tokenize text
  2. Fit data to the tokenizer
  3. Print the vocabulary of the tokenizer
  4. Encode 'Text' column
  5. Print the results

Løsning

Switch to desktopSkift til skrivebord for at øve i den virkelige verdenFortsæt der, hvor du er, med en af nedenstående muligheder
Var alt klart?

Hvordan kan vi forbedre det?

Tak for dine kommentarer!

Sektion 6. Kapitel 2
single

single

close

Awesome!

Completion rate improved to 3.33

bookChallenge 2

Stryg for at vise menuen

Opgave

Swipe to start coding

So, now let's remember what we do with text data. You will be working with the 'reviews.csv' dataset, and your task will be to encode text data using the bag of words method.

  1. Create a CountVectorizer object to tokenize text
  2. Fit data to the tokenizer
  3. Print the vocabulary of the tokenizer
  4. Encode 'Text' column
  5. Print the results

Løsning

Switch to desktopSkift til skrivebord for at øve i den virkelige verdenFortsæt der, hvor du er, med en af nedenstående muligheder
Var alt klart?

Hvordan kan vi forbedre det?

Tak for dine kommentarer!

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