Master AWS with our Essential Quiz

Which of the following is a benefit of using AWS to build your internet application?

What is the difference between a physical server and a virtual server on AWS?

What analogy does the text use to describe using AWS to build your internet application?

Which constructor can be used to create a Sequential model in Keras?

How can layers be added incrementally to a Sequential model in Keras?

What is the recommended approach to specify the input shape of a Sequential model in Keras?

A Guide to Sequential Models in Keras

Sequential models are appropriate for a simple stack of layers with one input and one output tensor.
The Sequential constructor can be used to create a Sequential model by passing a list of layers.
Layers in a Sequential model can be accessed using the layers attribute or added incrementally using the add() method.
The input shape of the model needs to be specified in advance for the layers to create their weights.
The summary() method can be used to display the contents of a built Sequential model.
An Input object can be passed to the model to specify the input shape from the start.
Debugging a Sequential model can be done by incrementally adding layers and printing the model summary.
Once a Sequential model is built, it can be used for feature extraction using the input and output attributes of each layer.
Transfer learning can be done by freezing the bottom layers and only training the top layers or stacking a pre-trained model with newly initialized classification layers.
Freezing layers can be done by iterating over model.layers and setting layer.trainable = False on each layer except the last one.
Stacking a pre-trained model with classification layers can be done by creating a new Sequential model and adding the pre-trained model's layers followed by the new classification layers.
It is recommended to specify the input shape of a Sequential model in advance if possible.

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