NLP-Intuition-and-Applications-of-word-embeddings

UPCOMING TUTORIAL on Word Representations and how they are important for NLP applications. The files and code will be uploaded soon!

If you would like to see any specific NLP application in the tutorial, like text classification, create an issue on this github. I will try to incorporate applications from issues in the tutorial.

The contents are as following :-

• The PDF document covers the intuition and the theory of word embeddings i.e. how we convert word meanings to numbers so that computers can understand them. This is the most important thing to read in this repository!
• The ipython notebook explores how these can be used in different NLP applications. Further, shows a comprehensive analysis of different methods on the same task of text classification.
• Easy_word_embeddings.py : word embeddings are used often and this file just makes loading them as easy as one line of code
• resource_list.txt : List of great resources to read on word embeddings.