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What is sequential modelling in Keras?
What is sequential modelling in Keras?
This recipe explains what is sequential modelling in Keras
Recipe Objective
In keras we can build model in two ways, one is Sequential API and other is Functional API. Here we will try understand Sequential API.
In Sequential API we can build a model by adding layers to it one by one. By adding layers we can make a stack of layers which will be interconnected and can be used.
We can make a sequential model by using the sequential module from the keras library. In which we can pass two arguments(args).
- layers : In this we can pass the optional list of layers that we want in the model
- name : In this we can give a name to the sequential model
keras.Sequential(layers=None, name=None)
Here is a short example of sequential model with two layers.
#Defining model
model = models.Sequential(layers=None, name=First_sequential_model)
#Adding layers
model.add(Dense(1024))
model.add(Dropout(0.5))
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