Question: Explain the purpose of the tf.keras.layers.Embedding layer.Answer: The Embedding layer is used for word embeddings in natural language processing tasks. It maps integer indices (representing words) to dense vectors, allowing the model to learn semantic relationships between words.Example: embedding_layer = tf.keras.layers.Embedding(input_dim=vocabulary_size, output_dim=embedding_dimension) |
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