Word2vec
Word2vec is a popular machine learning technique for generating vector embeddings based on the distributional properties of words in large corpora. It is directly relevant to vector databases as it produces the high-dimensional vector representations stored and indexed by these databases for vector search and similarity tasks.
About this tool
Word2vec
Category: SDKs & Libraries
Tags: vector-embeddings, machine-learning, open-source, python
Description
Word2vec is a widely used machine learning technique for generating vector embeddings of words, leveraging their distributional properties in large text corpora. It is relevant for applications involving vector databases, as it creates high-dimensional vector representations used for vector search and similarity tasks.
Features
- Generates vector embeddings for words based on their usage in large corpora
- Suitable for tasks such as word similarity, clustering, and semantic search
- Outputs high-dimensional vectors that can be indexed and searched in vector databases
- Open-source implementation
- Available in Python and other languages
Pricing
- Open-source (free to use)
Source
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