msb-public
/
ML-For-Beginners
mirror of https://github.com/microsoft/ML-For-Beginners.git
1
0
Code Issues Projects Releases Wiki Activity
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
Branches Tags
${ item.name }
Create tag ${ searchTerm }
Create branch ${ searchTerm }
from 'f16880941b'
${ noResults }
ML-For-Beginners/6-NLP
History
edgargonarr 90ce8e8a8f
Update README.md 		3 years ago
..
1-Introduction-to-NLP Update README.md 3 years ago
2-Tasks changes per request 3 years ago
3-Translation-Sentiment infographic for clarity 3 years ago
4-Hotel-Reviews-1 renaming NLP notebook 3 years ago
5-Hotel-Reviews-2 a few clarifications so notebooks will run 3 years ago
data notebook files and lesson writeup edits 3 years ago
images re-numbering lesson groups 3 years ago
translations Create README.zh-cn.md 3 years ago
README.md final NLP lesson, Learn collection link 3 years ago

README.md

Getting started with natural language processing

Natural language processing, NLP, is a subfield of artificial intelligence. 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.

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