oxford-cs-deepnlp-2017/practical-1
Oxford Deep NLP 2017 course - Practical 1: word2vec
This project helps natural language processing practitioners explore the meaning of words by training a 'word2vec' model. You provide a collection of text documents (like TED Talks or Wikipedia articles), and it outputs a numerical representation (an 'embedding') for each word. These embeddings capture semantic relationships, allowing you to find words with similar meanings or explore word clusters. It is designed for students or researchers in NLP.
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Use this if you are learning how to create, analyze, and visualize word embeddings from text data to understand semantic relationships between words.
Not ideal if you need a production-ready system for large-scale word embedding training or if you are not interested in the foundational mechanics of word2vec.
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Mar 08, 2021
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