Easier to train a model with d inputs than a model with N inputs Embeddings can be learned from data Dense representations - Inefficient in space and compute
Embedding
Feature columns (like layers)
latent features
Custom Estimator
Keras Models
High-level deep neural networks library (supports multiple backends)
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