• Different layers have different function
• Used for specific kind of tasks
• like Convolutional layers can be used to analyze image data
• Recurrent layers are used for time series data

Each node of the input layer represents individual feature from each sample of our data set

Each input node is connected to hidden layer nodes.

Each of these connections transfers the output from the previous unit to the next unit

Each connection has its own assigned weight. which can be a value between 1 and 0. 

weight represents the strength of the connection between the units

The output will be number between 0 and 1

The output layers represents categories 

• We will not specify in input layer in sequential object
• Note that in the second dense layers we don't have input shape that's because we don't specify the input shape to the next layers . 
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