Now, we have prepared our data for inmates classify it.
The next step is model creation.
There are two ways to create and train your model in Cadeaux.
The first one is the sequential Märta LaPier and the second one is the functional LaPier.
Sequential EPA is a straight forward and simple, whereas functional EPA is little bit complex, but
it will give you the flexibility to create some complex neural networks sequential.
EPA is useful to create layer by layer models such as these, where all the outputs of previous layer
are connected as inputs of the next layer and so on.
So for a simple neural network like this, sequential EPA is recommended.
But for some advanced complex, a structure such as this, here we are using input as an input for concat
layer as well.
So this layer have two inputs.
One, all of our primary input parameters and the outputs of hidden layer as well.
So anywhere if you want complex structure like this or you want to only use some part of your input
in one hidden layer and other part of input in some other hidden layer, for all such variations, you
can use functional LaPier.
But for a straight forward, dense neural networks like this, you can use sequential LaPier.
And this goes first, we will use the sequential LaPier.
Then we will also look at this example of functional Libya.