DerekChia/word2vec_numpy
Word2Vec implementation using numpy
This is a hands-on implementation of the Word2Vec algorithm, designed to help you understand how word relationships are numerically represented. It takes raw text data as input and produces vector representations (embeddings) of words, where words with similar meanings are closer together in the vector space. This is ideal for students, educators, or anyone looking to learn the foundational mechanics of natural language processing without relying on complex libraries.
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Use this if you are a student or educator wanting to deeply understand the mechanics of how Word2Vec works from scratch, using a simple, transparent implementation.
Not ideal if you need a high-performance, production-ready Word2Vec model or are looking to process large datasets efficiently.
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Language
Python
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Last pushed
Feb 11, 2020
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