embedding layer
时间: 2023-10-26 19:42:02 浏览: 47
An embedding layer is a neural network layer that maps input data to a lower-dimensional space, known as an embedding space. In natural language processing, embedding layers are commonly used to convert words or phrases into dense vectors of fixed size, which can be fed into further layers of a neural network for various tasks such as text classification, sentiment analysis, and language translation.
The embedding layer typically learns the mapping from the input data to the embedding space through the process of training the neural network on a large corpus of text data. The embedding space is chosen to have a lower dimensionality than the input data, which helps reduce the computational cost of subsequent layers in the network.
The main advantage of using an embedding layer is that it allows the neural network to capture the semantic meaning of the input data in a more compact and efficient form, which can improve the accuracy of downstream tasks.
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