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Step by step, we will:

  1. Use a Python script to randomly generate words from a dictionary.
  2. Build sentences by sampling these words using a Markov language model.
  3. Implement grammar rules parsed from the text of a large document set.
  4. Build data structures including linked lists, hash tables, stacks, queues, and heaps to store the words and sentences.
  5. Analyze the inner workings and performance tradeoffs of each data structure.
  6. Deploy your language model to a Flask web server on Heroku and connect it to Twitter to let users tweet their favorite results.