How to Use Word Embedding Layers for Deep Learning with Keras - Machine Learning Mastery(About) Keras Embedding Layer requires that the input data be integer encoded, so that each word is represented by a unique integer. This data preparation step can be performed using the Tokenizer API also provided with Keras.
The Embedding layer is initialized with random weights and will learn an embedding for all of the words in the training dataset.
- Example of Learning an Embedding
- Example of Using Pre-Trained GloVe Embedding