keras.sequential
from keras.models import Sequential
from keras.layers import Dense, Activation
model = Sequential([
Dense(32, input_shape=(784,)),
Activation('relu'),
Dense(10),
Activation('softmax'),
])keras.sequential
from keras.models import Sequential
from keras.layers import Dense, Activation
model = Sequential([
Dense(32, input_shape=(784,)),
Activation('relu'),
Dense(10),
Activation('softmax'),
])keras sequential layer
model = keras.Sequential(
[
layers.Dense(2, activation="relu"),
layers.Dense(3, activation="relu"),
layers.Dense(4),
]
)sequential layer keras
A Sequential model is appropriate for a plain stack of layers where each layer has exactly one input tensor and one output tensor.Copyright © 2021 Codeinu
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