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autoencoder in keras

Innocent Iguana answered on March 12, 2021 Popularity 2/10 Helpfulness 8/10

answer autoencoder in keras

related autoencoder for classification keras

autoencoder in keras

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### Creating Auto-encoder
# Instantiate a sequential model
autoencoder = Sequential()
# Add a hidden layer of 4 neurons and an input layer of 100
autoencoder.add(Dense(4, input_shape=(100,), activation='relu')) # The hidden layer with 4 neurons will strictly compress the information to learn
# Add an output layer of 100 neurons
autoencoder.add(Dense(100, activation='sigmoid'))
# Compile your model with the appropiate loss
autoencoder.compile(optimizer='adam', loss='binary_crossentropy')

### A separate model to encode inputs
# Building a separate model to encode inputs
encoder = Sequential()
encoder.add(autoencoder.layers[0]) # Only add the first hidden layer with 4 neurons
# This will return what the four hidden layer neuron sees as features for the test data
encoder.predict(X_test)

Popularity 2/10 Helpfulness 8/10 Language python

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Tags: autoencoder keras python

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Contributed on Apr 17 2024

Innocent Iguana

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autoencoder for classification keras

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for l1,l2 in zip(full_model.layers[:19],autoencoder.layers[0:19]):
    l1.set_weights(l2.get_weights())

Popularity 8/10 Helpfulness 1/10 Language python

Source: www.datacamp.com

Tags: classification autoencoder keras python ke

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Contributed on Mar 12 2021

Successful Stork

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autoencoder in keras

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