sismetanin/word2vec-tsne
Google News and Leo Tolstoy: Visualizing Word2Vec Word Embeddings using t-SNE.
This tool helps you visually explore how words relate to each other in large collections of text, like news articles or novels. It takes complex word patterns and turns them into easy-to-understand visual maps. If you're a linguist, a researcher analyzing text data, or anyone interested in the hidden connections between words, you can use this to see how language models interpret meaning.
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Use this if you want to understand the underlying relationships between words in your text data, visualizing how they cluster and interact.
Not ideal if you need to build or train a word embedding model from scratch, as this focuses on visualization rather than model creation.
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Last pushed
Nov 15, 2018
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