Check out how much you’ve learned about natural language processing!

  • Natural language processing combines computer science, linguistics, and artificial intelligence to enable computers to process human languages.
  • NLTK is a Python library used for NLP.
  • Text preprocessing is a stage of NLP focused on cleaning and preparing text for other NLP tasks.
  • Parsing is an NLP technique concerned with breaking up text based on syntax.
  • Language models are probabilistic machine models of language use for NLP comprehension tasks. Common models include bag-of-words, n-gram models, and neural language modeling.
  • Topic modeling is the NLP process by which hidden topics are identified given a body of text.
  • Text similarity is a facet of NLP concerned with semblance between instances of language.
  • Language prediction is an application of NLP concerned with predicting language given preceding language.
  • There are many social and ethical considerations to take into account when designing NLP tools.


You can build a lot of fun tools with NLP knowledge and a bit of Python. This is just the beginning.

Feel free to test out the plagiarism classifier we built in the code editor (does it work?) or use the space to play around with other NLP code you’ve encountered in this lesson!

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