ML-For-Beginners/6-NLP
Vidushi Gupta f5cc097211
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1-Introduction-to-NLP Fixed hyperlink 2023-06-08 12:31:50 +05:30
2-Tasks Fixed hyperlink 2023-06-08 12:35:06 +05:30
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translations (spanish): 6-NLP/README.md (#516) 2022-02-11 17:56:24 -05:00
README.md

README.md

Getting started with natural language processing

Natural language processing (NLP) is the ability of a computer program to understand human language as it is spoken and written -- referred to as natural language. It is a component of artificial intelligence (AI). NLP has existed for more than 50 years and has roots in the field of linguistics. The whole field is directed at helping machines understand and process the human language. This can then be used to perform tasks like spell check or machine translation. It has a variety of real-world applications in a number of fields, including medical research, search engines and business intelligence.

Regional topic: European languages and literature and romantic hotels of Europe ❤️

In this section of the curriculum, you will be introduced to one of the most widespread uses of machine learning: natural language processing (NLP). Derived from computational linguistics, this category of artificial intelligence is the bridge between humans and machines via voice or textual communication.

In these lessons we'll learn the basics of NLP by building small conversational bots to learn how machine learning aids in making these conversations more and more 'smart'. You'll travel back in time, chatting with Elizabeth Bennett and Mr. Darcy from Jane Austen's classic novel, Pride and Prejudice, published in 1813. Then, you'll further your knowledge by learning about sentiment analysis via hotel reviews in Europe.

Pride and Prejudice book and tea

Photo by Elaine Howlin on Unsplash

Lessons

  1. Introduction to natural language processing
  2. Common NLP tasks and techniques
  3. Translation and sentiment analysis with machine learning
  4. Preparing your data
  5. NLTK for Sentiment Analysis

Credits

These natural language processing lessons were written with by Stephen Howell