Free hands-on course with the implementation (in Python) and description of several Natural Language Processing (NLP) algorithms and techniques.

Although it is not intended to have the formal rigor of a book, we tried to be as faithful as possible to the original algorithms and methods, only adding variants, when these were necessary for didactic purposes.

Examples:

  1. NLP with spaCy
  2. Semantic Enrichment of Entities
  3. Spell Checker/Corrector
  4. Word Embedding with Gensim
  5. Relationship between Words

NLP Header

Click here to see the project and the repository.