Dense keras意思

"Dense" in Keras refers to a specific layer type in the Keras neural network library, which is part of the TensorFlow framework. The Dense layer is also known as a fully connected layer.

In a neural network, layers can be either fully connected (dense) or convolutional. A Dense layer connects every input to every output with a weight and a bias, which makes it different from convolutional layers that have local connections and weights sharing.

Here's a simple example of how a Dense layer might be used in a Keras model:

from keras.models import Sequential
from keras.layers import Dense

model = Sequential()
model.add(Dense(64, input_dim=784, activation='relu'))
model.add(Dense(128, activation='relu'))
model.add(Dense(10, activation='softmax'))

model.compile(optimizer='adam',
              loss='sparse_categorical_crossentropy',
              metrics=['accuracy'])

In this example, the Dense layers are used to create a simple feedforward neural network with two hidden layers. The first Dense layer has 64 neurons, the second has 128 neurons, and the output layer has 10 neurons (since there are 10 classes in the problem, e.g., for MNIST digits classification).

The "Dense" terminology is used because every input is connected to every output in the layer, which results in a dense network of connections.