Introduction to Deep Learning with Keras
Miguel Esteban
Data Scientist & Founder
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense
# Create a new sequential model model = Sequential()
# Add and input and dense layer model.add(Dense(2, input_shape=(3,)))
# Add a final 1 neuron layer model.add(Dense(1))
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense
# Create a new sequential model model = Sequential()
# Add and input and dense layer model.add(Dense(2, input_shape=(3,)))
# Add a final 1 neuron layer model.add(Dense(1))
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense
# Create a new sequential model model = Sequential()
# Add and input and dense layer model.add(Dense(2, input_shape=(3,), activation="relu"))
# Add a final 1 neuron layer model.add(Dense(1))
model.summary()
Layer (type) Output Shape Param #
=================================================================
dense_3 (Dense) (None, 2) 8
_________________________________________________________________
dense_4 (Dense) (None, 1) 3
=================================================================
Total params: 11
Trainable params: 11
Non-trainable params: 0
_________________________________________________________________
model.summary()
Layer (type) Output Shape Param #
=================================================================
dense_3 (Dense) (None, 2) --> 8 <--
_________________________________________________________________
dense_4 (Dense) (None, 1) 3
=================================================================
Total params: 11
Trainable params: 11
Non-trainable params: 0
_________________________________________________________________
Introduction to Deep Learning with Keras