Text Preprocessing Quiz

What is the main goal of preprocessing text data?

• To bring the text into a predictable and analyzable form

• To increase the size of the corpus

• To eliminate all words with similar meanings

• To make the text more complex

What does reducing the corpus of words exposed to the model help achieve?

• Makes the text less predictable

• Simplifies the analysis of the text

• Adds more noise to the data

• Increases the number of unique words

What is one of the tasks of text preprocessing?

• To remove all punctuation

• To convert text to uppercase

• To correlate words with different meanings

• To correlate words with similar meanings

Which function is mentioned for tokenization in Python?

• split()

• parse()

• tokenize()

• join()

Which library is mentioned for tokenization?

• NLTK

• Pandas

• NumPy

• Matplotlib

What is the first phase of the NLP pipeline mentioned?

• Data visualization

• Tokenization using Python’s split() function

• Model training

• Data cleaning

What does the text preprocessing aim to achieve?

• To create more complex data structures

• To bring the text into a form that is predictable and analyzable

• To increase the length of the text

• To eliminate all stop words

What is the second phase of the NLP pipeline?

• Data normalization

• Tokenization using NLTK

• Feature extraction

• Model evaluation

What is the purpose of explicitly correlating words?

• To confuse the model

• To correlate words with different meanings

• To enhance the model's understanding of similar meanings

• To reduce the number of words

What does tokenization involve?

• Changing the font of the text

• Removing all numbers from the text

• Combining words into sentences

• Breaking text into individual words or tokens