Embedding vector: Revision history

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18 March 2023

  • curprev 13:1513:15, 18 March 2023‎ Walle talk contribs‎ 3,376 bytes +3,376‎ Created page with "{{see also|Machine learning terms}} ==Introduction== An '''embedding vector''' in machine learning refers to a continuous, dense representation of discrete objects such as words, images, or nodes in a graph. Embedding vectors are used to convert these discrete objects into a continuous space, which makes it easier to apply machine learning algorithms that rely on mathematical operations. Typically, these embeddings are generated through unsupervised or supervised learnin..."
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