244 - What are embedding layers in keras?
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Embedding layer...
Maps each value in the input array to a vector of a defined size.
The weights in this layer are learned during the training process.
Initialization is performed (just like other keras layers).
One-hot encoding is inefficient as most indices are zero. (e.g., Text with 1000 words means most of the elements are 0)
Integer encoding does not reflect the relationship between words.
Embedding allows for the representation of similar words with similar encoding.
Values are learned (trainable).
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