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Damir Zunic

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NLP – Natural Language Processing with Python

The course is provided by Jose Portilla (Pierian Data Inc.). With 80 lectures and 11.5 hours of videos this course is designed to be the complete online resource for learning how to use Natural Language Processing with the Python programming language.

The course taught me:

  • how to work with text and PDF files within Python
  • how to use Regular Expressions for pattern searching in text
  • fundamental NLP concepts such as stemming, lemmatization, stop words, phrase matching, tokenization
  • how to use Spacy for ultra fast tokenization and vocabulary matching
  • how to use Part-of-Speech (POS) tagging to automatically process raw text files and understand named entity recognition (NER)
  • visualize POS and NER with Spacy in real time
  • machine learning with Scikit-learn to conduct text classification and topic modeling using Latent Dirichlet Allocation
  • sentiment analysis of text with the NLTK library, and creating semantic word vectors with the Word2Vec algorithm
  • how to use deep learning to build out chat bots

Credentials:

  • Certificate

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