TensorFlow 1.x Deep Learning Cookbook

How to do it...

We proceed with Keras as follows:

1. As the first step, we define the type of our model. Keras offers two types of models: sequential and Model class API. Keras offers various types of neural network layers:

# Import the model and layers needed  
from keras.model import Sequential 
from keras.layers import Dense 
 
model = Sequential() 

2. Add the layers to the model with the help of model.add(). Keras offers the option of a dense layer--for a densely connected neural network, layer Dense(units, activation=None, use_bias=True, kernel_initializer='glorot_uniform', bias_initializer='zeros', kernel_regularizer=None, bias_regularizer=None, activity_regularizer=None, kernel_constraint=None, bias_constraint=None). According to Keras documentation: ...