SKILL BENCHMARK

Fundamentals of Text Processing in NLP Literacy (Beginner Level)

  • 15m
  • 15 questions
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The Fundamentals of Text Processing in NLP Literacy (Beginner Level) benchmark measures your ability to recall and understand the basics of text preprocessing and cleaning in Natural Language Processing (NLP). You will be evaluated on your knowledge of the Natural Language Toolkit (NLTK), SpaCy, and Python libraries for text processing. A learner who scores high on this benchmark demonstrates that they have a basic understanding of the foundations of text processing in NLP.

Topics covered

  • compute similarity of words
  • explore types of words in WordNet
  • explore WordNet synsets
  • install NLTK and set up Python
  • list the preprocessing steps for natural language processing
  • perform lemmatization with NLTK
  • perform lemmatization with SpaCy
  • perform parts-of-speech (POS) tagging and named entity recognition (NER)
  • perform stemming with NLTK
  • perform tokenization with NLTK
  • perform tokenization with SpaCy
  • provide an overview of natural language processing and how it can be supported by the Natural Language Toolkit (NLTK) and SpaCy
  • remove stopwords using NLTK
  • remove stopwords using SpaCy
  • view the Gutenberg and Brown corpora in NLTK