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MLS-C01 · Question #53

A Machine Learning Specialist is creating a new natural language processing application that processes a dataset comprised of 1 million sentences. The aim is to then run Word2Vec to generate…

The correct answer is B. Normalize all words by making the sentence lowercase. C. Remove stop words using an English stopword dictionary. F. Tokenize the sentence into words. 1- Apply words stemming and lemmatization 2- Remove Stop words 3- Tokensize the sentences https://towardsdatascience.com/nlp-extracting-the-main-topics-from-your-dataset-using-lda-in- minutes-21486f5aa925

Data Engineering

Question

A Machine Learning Specialist is creating a new natural language processing application that processes a dataset comprised of 1 million sentences. The aim is to then run Word2Vec to generate embeddings of the sentences and enable different types of predictions. Here is an example from the dataset:

"The quck BROWN FOX jumps over the lazy dog." Which of the following are the operations the Specialist needs to perform to correctly sanitize and prepare the data in a repeatable manner? (Choose three.)

Options

  • APerform part-of-speech tagging and keep the action verb and the nouns only.
  • BNormalize all words by making the sentence lowercase.
  • CRemove stop words using an English stopword dictionary.
  • DCorrect the typography on "quck" to "quick."
  • EOne-hot encode all words in the sentence.
  • FTokenize the sentence into words.

How the community answered

(29 responses)
  • A
    3% (1)
  • B
    76% (22)
  • D
    7% (2)
  • E
    14% (4)

Explanation

1- Apply words stemming and lemmatization 2- Remove Stop words 3- Tokensize the sentences https://towardsdatascience.com/nlp-extracting-the-main-topics-from-your-dataset-using-lda-in- minutes-21486f5aa925

Topics

#NLP#Text Preprocessing#Word Embeddings#Data Preparation

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