Before explaining what is embedding layer in Keras, you need to know what exactly is word embeddings. Word embedding is better described as a set of approaches that transforms words or documents into a dense vector representation.
Now, Keras is a deep learning framework, in which an embedding layer needs all the words to be in the form of an integer so that it could represent them as vectors representation. This layer is flexible which could be used again after using in a model, which could learn embedding along with the training, and also it could be used as a pre-training word embedding model which is suitable for transfer of learning. The embedding layer is often considered as the first layer of a neural network.
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