Deep Learning with Keras

The first example of Keras code

The initial building block of Keras is a model, and the simplest model is called sequential. A sequential Keras model is a linear pipeline (a stack) of neural networks layers. This code fragment defines a single layer with 12 artificial neurons, and it expects 8 input variables (also known as features):

from keras.models import Sequentialmodel = Sequential()model.add(Dense(12, input_dim=8, kernel_initializer='random_uniform'))

Each neuron can be initialized with specific weights. Keras provides a few choices, the most common of which are listed as follows:

• random_uniform: Weights are initialized to uniformly random small values in (-0.05, 0.05). In other words, any value within the given interval is equally ...