TensorFlow Model Deployment

Deploy TensorFlow models to production environments using SavedModel format, TensorFlow Lite for mobile and edge devices, quantization techniques, and serving infrastructure. This skill covers model export, optimization, conversion, and deployment strategies.

SavedModel Export

Basic SavedModel Export

# Save model to TensorFlow SavedModel format
model.save('path/to/saved_model')

# Load SavedModel
loaded_model = tf.keras.models.load_model('path/to/saved_model')

# Make predictions with loaded model
predictions = loaded_model.predict(test_data)